Spark Jobs in Bengaluru

Position: Data Scientist (AI/ML Expert) Location: Pritech Park SEZ, Block 09, 4th Floor B Wing, Survey No. 51 to 64/4, Outer Ring Road, Bellandur V, Bangalore, Karnataka, India Department: Advanced Analytics Employment Type: Subexian Experience Required: 1 to 3 years Job Overview: We are looking for a talented Data Scientist with expertise in AI/ML to join our Advanced Analytics team. As a key contributor, you ll design, develop, and validate predictive models, recommendation systems, and forecasting solutions, while also collaborating with cross-functional teams to deliver cutting-edge solutions using the latest technologies. Key Responsibilities: Model Development: Design, develop, and validate predictive models, recommendation systems, and forecasting solutions using a mix of statistical, machine learning, and deep learning techniques. You will work both independently and as part of a collaborative team. Data Visualization & Reporting: Communicate actionable insights effectively through compelling dashboards, reports, and visualizations using tools such as Superset, Power BI, and Python libraries (Matplotlib, Seaborn, Plotly). AI & Tech Solutions: Collaborate with teams to design and deliver flexible, scalable solutions using advanced technologies such as AI and large language models (LLMs). API Development: Develop and integrate REST APIs and frameworks such as Flask or FastAPI for seamless deployment of machine learning models. Documentation: Maintain clear, comprehensive documentation for data workflows, model development, and analytical methodologies to ensure knowledge sharing and transparency across teams. Continuous Learning: Stay up-to-date with the latest trends and advancements in data science, algorithms, and technologies, ensuring your skills and knowledge remain cutting-edge. Required Technical Skills: Python Proficiency: Strong experience with Python and libraries like Scikit-learn, TensorFlow/PyTorch, and data visualization libraries (Matplotlib, Seaborn, Plotly). SQL: Solid hands-on experience in SQL for efficient data querying. ML Ops & Pipelines: Understanding of machine learning operations (ML Ops) and ML pipelines for streamlined model deployment. Cloud & Distributed Computing: Exposure to cloud platforms such as AWS, Azure, or GCP and distributed computing tools like Hadoop, Spark, or Pyspark is a plus. Soft Skills: Effective Communication: Strong ability to communicate complex analytical findings in a clear and engaging manner, tailoring insights for both technical and non-technical audiences. Problem-Solving: A proactive problem-solver with the ability to adapt and thrive in a fast-paced, dynamic environment. Continuous Growth: Self-motivated, curious, and always seeking opportunities for professional growth and learning. At Subex, we encourage a collaborative, innovative, and growth-driven work environment. If you're passionate about applying data science techniques to real-world challenges and want to work with cutting-edge AI/ML technologies, we d love to hear from you!

Senior Associate Data Engineering L2 Location: Bengaluru, India Department: Engineering Data Employment Type: Full-Time About the Role As a Senior Associate Data Engineering (L2) at Publicis Sapient, you will lead technical solutions that drive digital transformation by building scalable, high-performance data platforms. You ll be responsible for translating business and technical requirements into modern, data-centric solutions using Big Data technologies, cloud services (Azure), and advanced data engineering practices. Key Responsibilities Design and implement data ingestion, integration, and transformation processes from multiple heterogeneous sources in both batch and real-time. Build scalable data platforms using Hadoop stack components such as HDFS, Kafka, Spark, Hive, NiFi, Oozie, Airflow, Flink, and Storm. Develop real-time analytics, aggregation, and search features to support various data-driven applications. Collaborate closely with cross-functional teams on data infrastructure, computation frameworks, and data visualization. Apply cloud-native principles and Azure services to build and deploy data pipelines. Ensure performance optimization and data pipeline tuning. Work with NoSQL and MPP platforms like MongoDB, Cassandra, Redshift, Azure SQL DW, HBase, BigQuery. Contribute to infrastructure, automation, and DevOps for data pipelines using CI/CD practices. Ensure data governance, lineage, and cataloging using tools like Collibra or Alation. Required Qualifications 6 8 years of professional experience in software/data engineering. Minimum of 3 years hands-on experience with Big Data technologies. Strong programming expertise in Java (preferred), Scala, or Python. Expertise in the Hadoop ecosystem and real-time stream processing tools (Kafka, Pulsar, Spark Streaming, etc.). Hands-on experience with Azure data services (e.g., Data Factory, Synapse, ADLS, Databricks). Experience working with modern ETL tools (Informatica, Talend, etc.) and traditional RDBMS platforms (Oracle, PostgreSQL, SQL Server, MySQL). Bachelor's degree in Computer Science, Engineering, or related field. Nice to Have Certifications in Azure Data Engineer, GCP Big Data, or related cloud specializations. Experience with distributed messaging frameworks (ActiveMQ, RabbitMQ, Solace). Familiarity with microservices architecture and search technologies (Elasticsearch). Performance tuning of distributed data processing systems. Exposure to data governance, security, and metadata management. Benefits and Culture at Publicis Sapient Gender-neutral workplace policies 18 paid holidays annually Generous parental leave + new parent transition support Flexible work arrangements Access to Employee Assistance Programs (wellness & well-being) A dynamic culture focused on learning, creativity, and collaboration Qualification : Bachelor's degree in Computer Science, Engineering, or related field.

Job Title: Lead Data Scientist Location: Bangalore North, Karnataka, India Job Type: Full-Time Industry: Entertainment / Mobile Gaming About Us We are one of India s most exciting and fast-growing mobile gaming companies. Founded in 2014 and partnered with Modern Times Group (MTG), our vision is to create simple, impactful casual game experiences at massive scale. Our portfolio includes evergreen hits such as Daily Themed Crossword, WordTrip, WordJam, WordWars, WordTrek, TileMatch, and Jigsaw. We have built a global network of chart-topping games supported by powerful tech and analytics infrastructure that fuels rapid growth. Position Summary As a Lead Data Scientist in our Central Analytics team, you will play a critical role in shaping data-driven strategies that enhance player experience and business performance. This fast-paced role offers abundant opportunities to work alongside product leaders and game teams, transforming complex data into actionable insights that drive user acquisition, engagement, and monetization. Key Responsibilities Collaborate closely with product leaders to provide data-driven advisory on strategic decisions. Partner with game development teams to analyze gameplay data and generate actionable insights that improve user acquisition, engagement, and monetization. Perform advanced exploratory data analyses and ad-hoc reporting to identify trends, issues, and opportunities across our game portfolio. Design, execute, and lead data research projects, delivering practical recommendations based on rigorous statistical analyses. Drive continuous improvement in game performance through innovative machine learning models and analytics techniques. Requirements Bachelor s/Master s/PhD degree in Computer Science, Statistics, or a related field. Proven experience with machine learning, statistical modeling, and data science projects. Hands-on proficiency in Python and/or Spark for data manipulation, visualization, and building ML models. Strong SQL skills with experience querying large, complex datasets from data lakes or warehouses. Demonstrated ability to lead research projects and translate findings into actionable business recommendations. Excellent interpersonal skills and a collaborative approach to working with cross-functional teams. Knowledge of Deep Learning frameworks and techniques is highly desirable. Work with a top-tier gaming company known for its innovative and data-driven culture. Influence millions of users worldwide through impactful analytics. Collaborate with talented teams in a high-growth, dynamic environment. Access to cutting-edge tools and technologies for data science and machine learning. Competitive compensation and career growth opportunities. Qualification : Bachelors/Masters/PhD degree in Computer Science, Statistics, or a related field.

Job Title: Senior Manager Data Science, Data Modelling & Analytics Location: Bengaluru Department: Insights & Analysis About the Role: As a Senior Manager, you will lead a team of data scientists and analysts, driving the development and deployment of advanced analytics solutions that enable data-driven decision-making. This role blends strategic leadership with hands-on technical expertise, playing a critical part in delivering impactful insights and analytics across the organization. Key Responsibilities: Hands-On Technical Contribution: Design, develop, and deploy advanced machine learning models and statistical analyses to address complex business challenges. Utilize Python, R, SQL, and other tools to manipulate data and build predictive models. Manage end-to-end data pipelines including collection, cleaning, transformation, and visualization. Collaborate with IT and data engineering teams to integrate analytics solutions into production environments. Provide thought leadership on analytics solutions and metrics aligned with business needs. Team Leadership & Development: Lead, mentor, and manage a team of data scientists and analysts, fostering collaboration and innovation. Guide career development, conduct performance evaluations, and promote skill enhancement. Encourage continuous learning and adoption of best practices in data science methodologies. Strategic Planning & Execution: Collaborate with senior leadership to define and execute data science strategy aligned with business goals. Identify and prioritize high-impact analytics projects that deliver business value. Ensure timely and quality delivery of analytics solutions balancing scope and resources. Client Engagement & Stakeholder Management: Act as primary point of contact for clients, translating business challenges into data science solutions. Lead client presentations, workshops, and discussions, effectively communicating complex analytical concepts. Build and maintain strong client relationships, managing expectations and deliverables. Deliver regular reports and dashboards to senior management and stakeholders. Bridge communication between technical teams and business units to align analytics initiatives with organizational objectives. Cross-Functional Collaboration: Work closely with Business Intelligence, Market Analytics, and Data Engineering teams to integrate analytics into business processes. Translate complex insights into actionable recommendations for non-technical stakeholders. Facilitate data-driven workshops and presentations across the organization. Collaborate with support functions to provide timely leadership updates on operational metrics. Governance & Compliance: Ensure compliance with data governance policies and data privacy regulations (e.g., GDPR, PDPA). Implement best practices for data quality, security, and ethical analytics use. Stay abreast of industry trends and regulatory changes affecting data analytics. Qualifications: Education: Bachelor s or Master s degree in Data Science, Computer Science, Statistics, Mathematics, or related field. Experience: 12+ years in advanced analytics, data science, data modelling, machine learning, or related fields. 5+ years in leadership roles managing analytics teams and projects. Experience in BFSI, Hi-Tech, Retail, or Healthcare industries preferred. Experience with media data is a plus. Technical Skills: Proficiency in Python, R, SQL. Experience with data visualization tools like Tableau, Power BI. Familiarity with big data platforms (Hadoop, Spark) and cloud services (AWS, GCP, Azure). Strong knowledge of machine learning frameworks and libraries. Soft Skills: Excellent analytical and problem-solving skills. Strong communication and interpersonal abilities. Ability to influence and drive organizational change. Strategic thinker focused on business outcomes. Desirable Expertise: Advanced Analytics Techniques: Descriptive Analytics: Statistical analysis, data visualization. Predictive Analytics: Regression, time series forecasting, classification, market mix modelling. Prescriptive Analytics: Optimization, simulation modelling. Text Analytics: NLP, sentiment analysis. Machine Learning Techniques: Supervised Learning: Linear/logistic regression, decision trees, random forests, gradient boosting, SVMs. Unsupervised Learning: Clustering, PCA, anomaly detection. Reinforcement Learning: Q-learning, deep Q-networks. Generative AI & Large Language Models (Good to Have): Experience with GPT, Gemini, LLAMA, etc. for text generation, summarization, conversational agents. Hyperparameter tuning, prompt engineering, embeddings, fine-tuning. Additional Skills: Proficiency with Tableau or Power BI (advanced visualization). Strong data management, structuring, and harmonization skills.

Position Title: Lead AI/ML Engineer Location: Bengaluru Bellandur (GTP) Employment Type: Full-time Job Summary Synechron is seeking a seasoned Lead AI/ML Engineer to lead cutting-edge initiatives in artificial intelligence and machine learning. This role requires deep technical expertise in AI/ML, including deep learning, NLP, computer vision, and generative AI, combined with strong leadership skills to manage teams and drive innovation. You will collaborate closely with stakeholders to deliver high-impact solutions and play a key role in shaping the company s AI-driven digital transformation. Key Responsibilities Lead end-to-end development of AI/ML solutions across use cases involving machine learning, deep learning, computer vision, NLP, and generative AI. Design and implement scalable models and algorithms, ensuring performance, accuracy, and interpretability. Collaborate with product owners, engineers, and business stakeholders to align AI/ML initiatives with strategic objectives. Mentor and guide data scientists and ML engineers to elevate technical quality and delivery standards. Continuously evaluate emerging AI technologies, frameworks, and methodologies to enhance team capabilities. Contribute to innovation strategy by identifying new business opportunities driven by AI/ML. Ensure data and model governance, ethical AI practices, and responsible deployment of AI solutions. Required Skills & Tools Core Competencies: Strong hands-on experience in machine learning, deep learning, NLP, computer vision, and generative AI. Expertise in Python (primary), with additional knowledge of R, SQL, Java, or C++. Deep understanding of statistics, linear algebra, probability, and algorithm design. Frameworks & Tools: TensorFlow, PyTorch, Keras, OpenCV, Hugging Face, spaCy, Scikit-learn, etc. Data processing tools like Pandas, NumPy, and Spark. Version control and CI/CD tools (e.g., Git, MLflow, Docker, Airflow). Methodologies: Proficient in Agile development and model lifecycle management. Experience with productionizing AI models and deploying them on cloud platforms (AWS, Azure, GCP). Experience 8 12 years of experience in AI/ML, Data Science, or related domains. Minimum 8+ years in a leadership or technical lead role driving successful AI/ML initiatives. Proven record of delivering high-impact AI/ML projects at scale. Experience mentoring and managing AI/ML teams in collaborative, cross-functional environments. Day-to-Day Activities Direct and oversee AI/ML model development, validation, deployment, and monitoring. Review project designs, provide technical oversight, and conduct code/model reviews. Drive research and experimentation to apply novel AI methods to solve real-world problems. Support proposal development and client engagements with AI/ML subject matter expertise. Foster a culture of continuous learning, innovation, and data-driven thinking. Qualifications Bachelor s or Master s degree in Computer Science, Data Science, Artificial Intelligence, or a related field. Relevant certifications (e.g., TensorFlow, AWS Machine Learning, Azure AI Engineer) are a plus. Soft Skills Strong leadership, team management, and mentoring capabilities. Excellent communication and stakeholder engagement skills. Strategic thinking with a passion for innovation and emerging technologies. Ability to thrive in a dynamic, fast-paced environment and lead through ambiguity. Diversity & Inclusion at Synechron Synechron is committed to a diverse and inclusive workplace. Through our Same Difference DEI initiative, we celebrate unique backgrounds and perspectives while fostering a respectful, empowering environment. We welcome applications from candidates of all identities and provide support through mentoring, internal mobility, and flexible work arrangements. Qualification : Bachelors or Masters degree in Computer Science, Data Science, Artificial Intelligence, or a related field.

Data Architect Bangalore, India Location: Bangalore (Bengaluru) Experience: 10 to 15 Years Industry: IT & Data Systems Job Summary: We are seeking an experienced Data Architect with a strong background in designing and implementing enterprise-scale data solutions. The ideal candidate will have expertise in building data lakes, warehouses, and pipelines, with deep knowledge of cloud platforms, data management, and industry best practices. Key Responsibilities: Design, develop, and maintain complex data architectures including data lakes, data warehouses, data marts, and efficient schema design Build and optimize scalable data pipelines for extraction, transformation, and loading (ETL/ELT) processes Apply Agile methodologies in project delivery and collaborate within cross-functional teams Perform data profiling, cleansing, conversion, and ensure high-quality data management for both structured and unstructured data Implement CI/CD and Infrastructure as Code (IaC) practices using tools like GitHub, Jenkins, CloudFormation, and Azure Resource Manager Manage database systems and tools such as PostgreSQL, Oracle, Snowflake, Teradata, MongoDB, Hadoop, and others Utilize data modeling tools like Erwin, Power Designer, and Toad for effective data architecture design Leverage cloud platforms including AWS and Microsoft Azure, with hands-on experience in services like AWS Glue, DMS, Lambda, Azure Data Factory, Synapse, and Data Lake Storage Work with programming and scripting languages including SQL, PL/SQL, Python, Spark, YAML, and JSON Use containerization and automation tools such as Docker, Ansible, and NodeJS for efficient deployment Ensure compliance with cybersecurity principles and frameworks such as NIST Lead data governance initiatives and enforce best practices in data quality and security Preferred Qualifications: ITIL certification and experience with Agile methodology Knowledge of code review and version control best practices, especially in GitHub Familiarity with data science tools and AI/ML frameworks like R, Keras, or TensorFlow Experience with natural language processing (NLP) and machine learning concepts Background in regulated industries, with pharma manufacturing experience highly preferred Exposure to multi-site, global IT projects and manufacturing operations Lead innovative data architecture projects within a dynamic and fast-paced environment Work with cutting-edge cloud technologies and big data ecosystems Collaborate with global teams on impactful enterprise solutions Access to professional growth opportunities in data governance, AI, and cloud technologies

Role: Senior Analyst Data Engineering Location: Bengaluru, Karnataka, India Experience: 3 6 Years Employment Type: Permanent, Full-Time About the Role We are looking for a results-driven Senior Data Engineer to join our high-performing data team in Bengaluru. The ideal candidate will have 3 6 years of experience in data engineering, AI/ML implementation, and working with large-scale databases like Snowflake and Teradata. If you're passionate about driving data-powered insights, building scalable solutions, and applying advanced machine learning and AI techniques, we want to hear from you. Key Responsibilities Design, develop, and implement machine learning models to solve complex business challenges. Apply AI techniques, including generative AI, NLP, and computer vision, to improve analytics capabilities. Use Tableau, Power BI, and other tools to develop insightful, interactive data dashboards. Manage and optimize large datasets using platforms like Snowflake, Teradata, and SQL/NoSQL databases. Collaborate with business and technical teams to translate requirements into robust data engineering solutions. Guide junior data professionals and foster a culture of learning and innovation. Communicate analytical findings clearly to non-technical stakeholders. Stay current with the latest in data science, machine learning, cloud platforms, and big data technologies. Key Skills & Technologies Machine Learning & AI Techniques: Supervised & unsupervised learning, deep learning, neural networks Reinforcement learning, decision trees, random forests, clustering NLP, computer vision, GANs, transfer learning Data Visualization Tools: Tableau, Power BI, Matplotlib, Seaborn, Plotly Programming Languages & Libraries: Python (essential), R, SQL TensorFlow, PyTorch, scikit-learn, pandas, NumPy, Keras, SciPy Databases & Data Management: Snowflake, Teradata, SQL/NoSQL, ETL, data lakes, data warehousing Cloud Platforms: AWS, Azure, Google Cloud Platform (GCP) Big Data Technologies: Apache Spark, Hadoop

Position: Senior Data Scientist Location: Bangalore Employment Type: Full-time Experience Required: 5 to 7 years Purpose of the Position: The Senior Data Scientist will play a key role in designing, developing, and implementing machine learning models and algorithms to solve complex business problems. The role involves collaborating with data scientists, software engineers, and business stakeholders to deliver scalable, efficient machine learning solutions that drive innovation and improve business outcomes. Key Responsibilities: Model Development and Optimization: Develop, train, and optimize machine learning models to meet business objectives. Ensure models are accurate, efficient, and scalable. Data Pipeline and Infrastructure: Design and maintain robust data pipelines to support machine learning workflows. Ensure data quality and integrity throughout the data lifecycle. Deployment and Monitoring: Deploy machine learning models into production. Monitor model performance and implement improvements as needed. Collaboration and Communication: Work with cross-functional teams to understand business requirements and translate them into technical solutions. Communicate complex technical concepts to non-technical stakeholders. Research and Innovation: Stay up to date with the latest advancements in machine learning and AI. Experiment with new techniques and technologies to enhance the organization's capabilities. Essential Skills: Machine Learning Frameworks: Experience with ML frameworks such as TensorFlow, PyTorch, and Scikit-learn. Programming Languages: Strong skills in Python and R. Data Processing: Experience with tools like Pandas, NumPy, and Spark. Model Deployment: Experience with Docker, Kubernetes, MLflow, and FastAPI. Databases: Strong experience in databases like Snowflake, MongoDB, and Cosmo DB. Statistical Analysis: Strong foundation in statistics and probability. Model Management: Experience establishing model management, monitoring, support, and maintenance frameworks. ML Lifecycle: Experience setting up ML lifecycle processes and governance policies, as well as providing L0, L1, and L2 support. Desired Skills: Deep Learning: Familiarity with deep learning frameworks like TensorFlow or PyTorch. Natural Language Processing (NLP): Understanding of NLP techniques and applications. Cloud Computing: Experience with cloud platforms like AWS, Azure, or Google Cloud. Big Data Technologies: Knowledge of big data technologies such as Hive, Pig, or Cassandra. Software Engineering: Proficiency in software development and version control systems like Git. Qualifications: Education: Master's degree or Ph.D. in Computer Science, Data Science, Statistics, Mathematics, or a related field. Experience: Over 5 years of experience in machine learning, with a proven track record of developing and deploying models. Certifications: Relevant certifications in machine learning or data science are a plus. Key Qualities: Analytical Thinking: Strong analytical and problem-solving skills. Communication: Excellent verbal and written communication skills. Team Player: Ability to work effectively in a collaborative team environment. Adaptability: Flexibility to adapt to changing business needs and technologies. Innovation: A proactive approach to exploring new ideas and technologies. Apply now to join our dynamic team and lead innovation through machine learning and AI! Qualification : Master's degree or Ph.D. in Computer Science, Data Science, Statistics, Mathematics, or a related field.

Job Title: Data Engineer Location: Bengaluru, Karnataka Experience: 5 to 8 Years Work Modality: Full-time (Work from office) Job Description: We are looking for an experienced Data Engineer to join our team and take responsibility for designing, developing, and maintaining scalable ETL/ELT pipelines. This is a full-time position based in Bengaluru, Karnataka, and you will be collaborating with cross-functional teams to define data requirements and ensure data accuracy, consistency, and integrity. Your role will also involve optimizing data workflows, automating processes, and ensuring high availability and reliability of data pipelines. Key Responsibilities: ETL/ELT Pipeline Development: Design, develop, and maintain scalable ETL/ELT pipelines to support data transformation and integration processes. Data Warehouse & Data Lake Optimization: Build and optimize data warehouses, data lakes, and real-time streaming solutions to support large-scale data operations. Collaboration & Data Requirements: Collaborate with cross-functional teams, such as product, data science, and analytics teams, to define data requirements and ensure data accuracy and consistency. Database Structure & Schema Management: Develop and maintain database structures and schemas to ensure efficient data storage and retrieval. Data Workflow Optimization: Optimize data workflows for performance, reliability, and scalability, ensuring the highest level of efficiency. Data Security & Compliance: Implement data security, governance, and compliance best practices to ensure that data is handled securely and meets industry standards. Pipeline Monitoring & Troubleshooting: Monitor, troubleshoot, and improve data pipelines to ensure uptime, reliability, and smooth data processing. Process Automation: Automate data-related processes to improve efficiency and reduce manual intervention, increasing the overall speed of data flow. Required Qualifications: Experience: 5+ years of experience in data engineering or 3-4 years of experience as a Data Engineer. Technical Skills: Strong proficiency in SQL and database management systems such as PostgreSQL, MySQL, SQL Server, etc. Experience with ETL tools such as Pentaho, Talend, Cdata, and SSIS. Exposure to Python, Java, or Scala for data processing is a plus. Experience with big data technologies such as Apache Spark, Hadoop, or Kafka. Familiarity with cloud services (AWS, Azure) and data storage solutions such as S3, Redshift, Snowflake, or BigQuery. Strong knowledge of data modeling, warehousing concepts, and data architecture best practices. Soft Skills: Excellent communication skills with the ability to collaborate effectively across teams. Strong problem-solving skills and the ability to work with large, complex datasets. What We Offer: Competitive Salary: Attractive salary based on experience and expertise. Collaborative Work Environment: Work in a dynamic and fast-paced environment with a team that fosters innovation and collaboration. Growth Opportunities: Opportunities to enhance your skills and career growth in the data engineering field. Comprehensive Benefits: Benefits package designed to support work-life balance and overall employee well-being.

Job Title: Data Scientist Location: Bengaluru Experience: 4+ Years About Linarc: Linarc is revolutionizing the construction industry. As the emerging leader in construction technology, we are redefining how projects are planned, executed, and delivered. Built for general contractors, construction managers, and trade partners, Linarc offers a next-generation platform that delivers unmatched collaboration, automation, and real-time intelligence to construction projects. Our mission is to eliminate inefficiencies, streamline workflows, and drive profitability, empowering teams to deliver projects faster, smarter, and with greater control. Join us in shaping the future of construction tech. If you thrive in a dynamic, fast-growing environment and want to make a significant impact, Linarc is the place for you. This is a full-time position based in Bengaluru. Roles and Responsibilities: Data Analysis & Modeling: Develop and implement machine learning models to address complex business problems. Build predictive models and algorithms to forecast customer behavior, product usage, and business outcomes. Conduct statistical analysis and hypothesis testing to uncover key insights and trends. Data Engineering & Processing: Clean, preprocess, and transform large-scale datasets from multiple sources. Design and optimize data pipelines for both real-time and batch processing. Business Insights & Reporting: Collaborate with business teams to define key performance indicators (KPIs). Develop dashboards and reports to effectively communicate findings and business performance. Present actionable insights and recommendations to stakeholders and leadership teams. Product Improvement: Partner with product managers to integrate data-driven insights into product features. Monitor model performance and continuously improve accuracy and scalability. Run A/B tests to evaluate the impact of product changes and optimize user experience. Research & Development: Stay updated with the latest developments in machine learning, artificial intelligence, and data science. Explore and implement new techniques and tools to drive innovative solutions and improve outcomes. Qualifications: Minimum Experience: 3 years of professional experience in Data Analytics, Data Science, AI, or Machine Learning. Technical Expertise: Deep analytical expertise in applying statistical solutions to business problems. Experience with exploratory data analysis of large datasets using tools like SQL, Hive, Spark, or similar. Proficiency in machine learning and deep learning tools such as Scikit-learn, TensorFlow, PyTorch, and familiarity with techniques like Neural Networks, Gradient Boosting, Logistic Regression, Decision Trees, Random Forests, Support Vector Machines, Clustering, etc. Experience working with visualization tools such as Tableau and Power BI. Business & Innovation: Demonstrated ability to innovate solutions and solve business problems using data science techniques. Desirable Additional Experience: 4+ years of experience in data science or machine learning in a product-focused environment. Experience working with relational or document databases. Proficiency in C, Python, PyTorch, Java, JavaScript, Node.js, React.js, or Vue.js. Strong knowledge of hypothesis testing and regression analysis. Experience in a SaaS product environment. Educational Qualifications: Bachelor s/Master s degree in Computer Science, Data Science, Mathematics, Statistics, or a related field.

Job/Position Summary: Data Engineer Responsibilities: Implement data pipelines that meet design and are efficient, scalable, and maintainable. Implement best practices including proper use of source control, participation in code reviews, data validation and testing. Timely deliveries while working on projects. Act as advisor/mentor and helps junior data engineers in their deliverables. Must Have Skills: Should have experience of at least 4+ years with Data Engineering. Strong experience of design, implementation and fine-tuning big data processing pipelines in production environment. Experience with big tools like Hadoop, Spark, Kafka, Hive, Databricks. Experience in programming at least one of with Python, Java, Scala, Shell Script. Experience with relational SQL and NO SQL databases like PostgresSQL, MYSQL, Cassandra etc. Experience with any data visualization tool (Plotly, Tableau, Power BI, Google Data Studio, Quick sight etc.). Good To Have Skills: Should have Basic Knowledge of CI/CD Pipeline. Experience in working on at least one Cloud (AWS or Azure or GCP). For AWS: - Experience with AWS Cloud services like EC2, S3, EMR, RDS, Athena, Glue, Lambda, EMR. For Azure: -Experience with Azure Cloud services like Azure Blob/Data Lake GEN2, Delta Lake, Databricks, Azure SQL, Azure DevOps, Azure Data Factory, Power BI. For GCP: - Experience with GCP Cloud services Big Query, Cloud Storage bucket, DataProc, Dataflow, Pub Sub, Cloud Function, Data Studio. Sound familiarity in Versioning tools (Git, SVN etc.). Experience Mentoring students is desirable. Knowledge of latest developments in Machine Learning, Deep Learning, Optimization in Automotive domain. Open minded approach to explore multiple algorithms to design optimal solution. History of contribution to articles/blogs/whitepapers etc. in Analytics. History of contribution to Open Source. Requirement: ESSENTIAL SKILLS /COMPETENCIES Data Engineering Hadoop Kafka CI/CD Cloud

Your Impact As a Data Engineer at QuantumBlack, you will collaborate with stakeholders, data scientists, and internal teams to develop and implement impactful data products and solutions. Your key responsibilities will include building and maintaining technical platforms for advanced analytics, designing scalable and reproducible data pipelines for machine learning, and ensuring information security within data environments. You will assess clients' data quality, map data fields to hypotheses, and prepare data for use in analytics models. Additionally, you will contribute to R&D projects, internal asset development, and participate in cross-functional problem-solving sessions with a variety of stakeholders, including C-level executives, to create innovative analytics solutions. You will be based in Gurugram, joining a global data engineering community, and work within cross-functional and Agile project teams alongside project managers, data scientists, machine learning engineers, other data engineers, and industry experts. You will collaborate directly with our clients, ranging from data owners and users to C-level executives. You will be aligned with one of our industry-focused practices: Pharma & Medical Products (PMP) or Global Energy & Materials (GEM). In these practices, you ll work on solving the most critical challenges for our clients in these sectors. PMP focuses on advancing the development and delivery of life-saving medicines and medical treatments, while GEM supports industries like chemicals, steel, mining, and energy to achieve operational excellence. GEMx and PMPx, the assetization arm of these practices, focus on creating reusable digital and analytics assets to support client work. As part of this team, you will help shape impactful solutions for large organizations, developing capabilities for sustained impact. Your Growth In this role, you will contribute to the frameworks and libraries that our teams of Data Scientists and Engineers use to progress from data to meaningful impact. You will have the opportunity to guide global companies through data science solutions, helping them transform and enhance performance across industries including healthcare, automotive, energy, and elite sports. Real-World Impact: You ll gain unique learning and development opportunities globally. Fusing Tech & Leadership: Work with the latest technologies and methodologies, with access to top-tier learning programs. Multidisciplinary Teamwork: Collaborate with data scientists, engineers, project managers, UX designers, and more to enhance performance. Innovative Work Culture: Creativity, passion, and wellness are central to our modern work environment, which includes insightful talks, training sessions, and a focus on work-life balance. Striving for Diversity: We celebrate diversity, with colleagues from over 40 nationalities, appreciating the value that diverse perspectives bring to the workplace. You are a highly collaborative individual who prioritizes impact over agenda. You enjoy learning from colleagues, challenging ideas thoughtfully, and working together to improve processes and solve problems. You believe in iterative change, experimenting with new approaches, and advancing quickly through constant learning and improvement. While we value using the right tech for the right task, our team often leverages technologies such as Python, PySpark, SQL, Airflow, Databricks, Kedro (our open-source data pipelining framework), Dask/RAPIDS, Docker, Kubernetes, and cloud solutions like AWS, GCP, and Azure. Your Role as a Data Engineer Collaboration: Work with business stakeholders, data scientists, and internal teams to create extraordinary, domain-focused data products (reusable assets) and deliver them to clients. Domain Expertise: Develop deep understanding of client industries and use creative techniques to deliver meaningful impact. Technical Platforms: Build and maintain technical platforms for advanced analytics engagements, spanning both data science and data engineering work. Data Pipelines: Design and implement robust, modular, scalable, deployable, and reproducible data pipelines for machine learning. Data Management: Ensure the security of data environments and compliance with information security standards. Data Wrangling: Assess data quality, map data fields to hypotheses, and prepare data for analytics models. Contribute to R&D: Participate in internal asset development and contribute to R&D projects to drive innovation. Cross-functional Problem Solving: Collaborate with internal teams and clients, including data owners and C-level executives, to create impactful analytics solutions. Your Qualifications and Skills Bachelor s degree in computer science or related field; Master's degree is a plus. 2-5 years of relevant work experience. Proficiency in at least one programming language such as Python, Scala, or Java. Strong experience with distributed processing frameworks (e.g., Spark, Hadoop, EMR) and SQL. Experience in commercial client-facing projects, particularly in close-knit teams. Ability to work with structured, semi-structured, and unstructured data, and identify linkages across disparate data sets. Clear communication skills to explain complex solutions effectively. Understanding of information security principles to ensure compliant handling of client data. Experience with cloud platforms (AWS, Azure, Google Cloud, Databricks) is highly desirable. Experience with CI/CD processes using GitHub Actions, CircleCI, or similar, and end-to-end pipeline development including application deployment is a plus. Qualification : Bachelors degree in computer science or related field; Master's degree is a plus.

As a Manager of the Spark Technical Solutions team, you will lead & manage a team of Technical solution engineers and be responsible for driving deep dive technical solutions for any issues reported by Databricks customers. We expect the manager to resolve challenges with comprehensive technical and customer communication skills. You will assist our customers in their Databricks journey and provide them with the guidance, knowledge, and expertise that they need to realise value and achieve their strategic objectives using our products. The impact you will have: As a manager and member of the leadership team, you will be directly responsible for the management of Technical solution engineers, team leads and operations personnel Responsible for directly monitoring, reporting, and driving improvements to team-level metrics and KPIs, acting as an escalation point with customers and internal teams, and optimising and developing support processes and tools Responsible for working across multiple cross functional teams that include Engineering, product management, sales and customer success; manage Hiring, mentoring and onboarding new support engineers Regularly meet one-on-one with your direct reports, conducting annual reviews and career development discussions throughout the year Be a hands on manager to assist the team members in resolving issues related to Spark core internals, Spark SQL, Structured Streaming, Delta, Lakehouse and other databricks runtime features Manage and drive best practices guidance around Spark runtime performance and usage of Spark core libraries and APIs for custom-built solutions developed by Databricks customers; contribute in the development of tools/automation initiatives Own Engineering JIRA tickets and proactively work to bring quicker resolutions to customer reported issues; participate in creation of knowledge base articles Participate in weekend and weekday on-call rotation and run escalations during databricks runtime outages, incident situations, ability to multitask and plan day 2 day activities and provide escalated level of support for critical customer operational issues, etc What we look for: Min 10-12 years of experience in designing, building, testing, and maintaining Python/Java/Scala/Spark based applications in a typical project delivery and consulting environments with 4+ years working as a Manager 5+ years of hands-on experience in developing and leading any two or more of the Big Data, Hadoop, Spark,Machine Learning, Artificial Intelligence, Streaming, Kafka, Data Science, ElasticSearch related industry use cases at the production scale. Spark experience is mandatory Hands on experience in the performance tuning/troubleshooting of Hive and Spark based applications at production scale. Real time experience in JVM and Memory Management techniques such as Garbage collections, Heap/Thread Dump Analysis is preferred Working and hands-on experience with Data lakes and any SQL-based databases, Data Warehousing/ETL technologies like Informatica, DataStage, Oracle, Teradata, SQL Server, MySQL is preferred Hands-on experience with AWS or Azure or GCP is preferred Experience in implementing CI/CD, Monitoring/alerting for Production Systems Technical lead in design, implementation and support of large scale data and analytics solutions that are highly reliable, flexible, and scalable Experience in leading and managing end-to-end projects and have reported and escalated to top levels Experience in managing and leading teams in an organisation involving multiple reporting lines Strong written and verbal communication skills; very good analytical, organisational, multi-tasking skills About Databricks Databricks is the data and AI company. More than 10,000 organizations worldwide including Comcast, Cond Nast, Grammarly, and over 50% of the Fortune 500 rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark , Delta Lake and MLflow. To learn more, follow Databricks on Twitter,LinkedIn and Facebook . Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region, please visithttps://www.mybenefitsnow.com/databricks. Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.

As a Senior Manager of the Spark Technical Solutions team, you will lead & manage a team of Technical Solution Engineers (Spark) and be responsible for driving deep dive technical solutions for any issues reported by Databricks customers. We expect the manager to resolve challenges with comprehensive technical and customer communication skills. You will assist our customers in their Databricks journey and provide them with the guidance, knowledge, and expertise that they need to realise value and achieve their strategic objectives using our products. The impact you will have: As a manager and member of the leadership team, you will be directly responsible for the management of Technical solution engineers, team leads and operations personnel Responsible for directly monitoring, reporting, and driving improvements to team-level metrics and KPIs, acting as an escalation point with customers and internal teams, and optimising and developing support processes and tools Responsible for working across multiple cross functional teams that include Engineering, product management, sales and customer success; manage Hiring, mentoring and onboarding new support engineers Regularly meet one-on-one with your direct reports, conducting annual reviews and career development discussions throughout the year Be a hands on manager to assist the team members in resolving issues related to Spark core internals, Spark SQL, Structured Streaming, Delta, Lakehouse and other databricks runtime features Manage and drive best practices guidance around Spark runtime performance and usage of Spark core libraries and APIs for custom-built solutions developed by Databricks customers; contribute in the development of tools/automation initiatives Own Engineering JIRA tickets and proactively work to bring quicker resolutions to customer reported issues; participate in creation of knowledge base articles Participate in weekend and weekday on-call rotation and run escalations during databricks runtime outages, incident situations, ability to multitask and plan day 2 day activities and provide escalated level of support for critical customer operational issues, etc What we look for: Min 10-12 years of experience in designing, building, testing, and maintaining Python/Java/Scala/Spark based applications in a typical project delivery and consulting environments with 4+ years working as a Manager 5+ years of hands-on experience in developing and leading any two or more of the Big Data, Hadoop, Spark,Machine Learning, Artificial Intelligence, Streaming, Kafka, Data Science, ElasticSearch related industry use cases at the production scale. Big Data / Spark hands on-experience is mandatory Hands on experience in the performance tuning/troubleshooting of Hive and Spark based applications at production scale. Real time experience in JVM and Memory Management techniques such as Garbage collections, Heap/Thread Dump Analysis is preferred Working and hands-on experience with Data lakes and any SQL-based databases, Data Warehousing/ETL technologies like Informatica, DataStage, Oracle, Teradata, SQL Server, MySQL is preferred Hands-on experience with AWS or Azure or GCP is preferred Experience in implementing CI/CD, Monitoring/alerting for Production Systems Technical lead in design, implementation and support of large scale data and analytics solutions that are highly reliable, flexible, and scalable Experience in leading and managing end-to-end projects and have reported and escalated to top levels Experience in managing and leading teams in an organisation involving multiple reporting lines About Databricks Databricks is the data and AI company. More than 10,000 organizations worldwide including Comcast, Cond Nast, Grammarly, and over 50% of the Fortune 500 rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark , Delta Lake and MLflow. To learn more, follow Databricks on Twitter,LinkedIn and Facebook . Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region, please visithttps://www.mybenefitsnow.com/databricks. Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.

Mission As a Spark Backline Engineer you will help our customers to be successful with the Databricks Data Intelligence platform by resolving important technical customer escalations and the support team. You will be the technical bridge between support and engineering and the first line of defense for engineering. You will ensure that all issues are vetted by you before it reaches the engineering team. You will report to the Senior Backline Manager of the Backline Escalations Team. Outcomes Troubleshoot, resolve and suggest deep code-level analysis of Spark to address complex customer issues related to Spark core internals, Spark SQL, Structured Streaming and Databricks Delta. Provide best practices guidance around Spark runtime performance and usage of Spark core libraries and APIs for custom-built solutions developed by Databricks customers. Help the support team with detailed troubleshooting guides and runbooks. Contribute to automation and tooling programs to make daily troubleshooting efficient. Work with the Spark Engineering Team and spread awareness of upcoming features and releases. Identify Spark bugs and suggest possible workarounds. Demonstrate ownership and coordinate with engineering and escalation teams to achieve resolution of customer issues and requests Participate in weekend and weekday on call rotation. Competencies Minimum 5 years' experience developing, testing, and sustaining Python or Java or Scala-based applications. Comfortable with compiling, building and navigating the Apache Spark source code. Comfortable with identifying and applying patches/bug fixes to the Apache Spark source code. Experience in Big Data/Hadoop/Spark/Kafka/Elasticsearch data pipelines. Hands-on experience with SQL-based database systems. Experience in JVM, GC, Thread dump-based troubleshooting is required. Experience with AWS or Azure related services. Bachelor's degree in Computer Science or a related field is required. About Databricks Databricks is the data and AI company. More than 10,000 organizations worldwide including Comcast, Cond Nast, Grammarly, and over 50% of the Fortune 500 rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark , Delta Lake and MLflow. To learn more, follow Databricks on Twitter,LinkedIn and Facebook . Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region, please visithttps://www.mybenefitsnow.com/databricks. Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone. Qualification : Bachelor's degree in Computer Science or a related field is required.

Position: Mechatronics & Big Data Scientist Developer Department: Research & Development Reporting To: General Manager Location: Bengaluru Key Responsibilities Machine Learning: Select features, build, and optimize classifiers using advanced machine learning techniques. Data Mining: Perform data mining using state-of-the-art methods to extract valuable insights from large datasets. Data Enhancement: Extend the company s datasets with third-party data sources when necessary to improve model accuracy and relevance. Data Collection & Processing: Improve data collection procedures to include all necessary information for building analytic systems. Data Cleansing & Integrity: Process, cleanse, and verify the integrity of data used for analysis to ensure reliable results. Ad-hoc Analysis: Perform ad-hoc analysis as needed, presenting the results in a clear, actionable manner. Anomaly Detection: Design and implement automated anomaly detection systems, tracking their performance over time to ensure accuracy. Behavioral Competencies Data-Driven: Strong inclination toward working with data and applying analytical thinking to solve complex problems. Detail-Oriented: Meticulous in data analysis and system development to ensure quality and precision in results. Skills and Expertise Machine Learning Algorithms Strong understanding of machine learning techniques and algorithms such as k-NN, Naive Bayes, SVM, Decision Forests, etc. Data Science Tools Experience with common data science toolkits like R, Weka, NumPy, and MatLab. Proficiency in at least one (preferably NumPy or R) is highly desirable. Data Visualization Skilled in data visualization tools such as D3.js, GGplot, or similar. Database Management Experience with query languages such as SQL, Hive, Pig, NiFi, or others depending on the company s stack. Familiarity with NoSQL databases like InfluxDB, MongoDB, Cassandra, HBase. Statistical Analysis Strong applied statistics skills, including distributions, statistical testing, and regression analysis. Programming Skills Good scripting and programming skills in languages like PHP, Slim, SQL, and Laravel. Big Data Technologies Knowledge of Hadoop, HDFS, NiFi, and other big data platforms and technologies. Qualifications Essential: MTech, MS, or equivalent in Mechatronics, Computer Science, or a related field. Experience: Minimum 2 years of hands-on experience in developing SDKs and working with Big Data platforms. Proven track record in machine learning, data mining, and data science projects. Qualification : MTech, MS, or equivalent in Mechatronics, Computer Science, or a related field

Analytics Engineer Location: Bengaluru Work Type: Full-Time About Postman Postman is the world s leading API platform, used by over 40 million developers and 500,000 organizations, including 98% of the Fortune 500. Our mission is to build an API-first world, simplifying every step of the API lifecycle and enabling teams to create better APIs, faster. Founded in Bengaluru, Postman is headquartered in San Francisco, with offices in Boston, New York, and Bengaluru. We are privately held, backed by Battery Ventures, BOND, Coatue, CRV, Insight Partners, and Nexus Venture Partners. The Opportunity We are seeking an Analytics Engineer to join our Data Team and help strengthen the foundation of our modern data stack. In this role, you will own critical transformation pipelines, design scalable data models, and ensure that our analytics environment is performant, reliable, and future-ready. You will operate with a high degree of independence, driving projects from design through production, while implementing best practices in dbt, semantic layers, medallion architecture, and lakehouse paradigms. Key Responsibilities Take ownership of large portions of our dbt project (3k+ models), ensuring scalability, maintainability, and adherence to best practices. Design and implement robust data models, including dimensional modeling, incremental strategies, and Slowly Changing Dimensions (SCDs). Establish and enforce dbt test coverage, automated quality checks, and CI/CD pipeline standards using GitHub Actions. Profile and optimize SQL queries and warehouse performance for efficiency and cost reduction. Build and refine our semantic layer, ensuring consistent business logic across Looker, Redash, and downstream tools. Collaborate with analysts and business partners to define metrics and deliver self-serve data assets. Document models, lineage, and transformation logic to make data discoverable and usable across the company. Contribute to shaping team standards and playbooks, collaborating with analysts on modeling and transformation best practices. Stay ahead of modern data stack innovations, including dbt metrics layer, universal semantic layers, data contracts, and observability. Enabling Self-Serve Analytics & AI Build transformations that empower business stakeholders and analysts to explore data confidently. Ensure metric definitions are consistent, discoverable, and reusable across BI tools. Prepare clean, structured, and accessible datasets for AI-driven initiatives like conversational analytics and anomaly detection. Partner with Data Science & ML teams to provide reliable pipelines that accelerate experimentation and AI/ML deployment. About You 3 5 years of experience in analytics engineering roles. Advanced SQL skills (query optimization, performance tuning). Strong proficiency in dbt Core: models, macros, snapshots, sources, and custom materializations. Solid background in data modeling techniques (Kimball, SCD handling, incremental pipelines). Practical experience with semantic layers and BI integration (LookML, dbt metrics, or equivalent). Familiarity with Medallion architecture and modern lakehouse approaches. Hands-on experience with Redshift; exposure to Databricks is a plus. Proficiency with GitHub and CI/CD pipelines for analytics code. Strong fundamentals in data quality, governance, and lineage tracking. Flexible schedule with a hybrid work model. Full medical coverage, flexible PTO, wellness reimbursement, and monthly lunch stipend. Access to wellness programs, team-building events, and donation-matching initiatives. An inclusive, collaborative culture where everyone can thrive and grow. Our Values Curiosity: Explore and innovate fearlessly. Transparency: Communicate openly about successes and failures. Focus: Set clear goals aligned with a bold vision. Inclusion: Every voice matters. Excellence: Deliver the best products and experiences together.

Senior Data Engineer Enterprise Data Platform Location: Bengaluru Department: Business Technology Data Engineering Experience: 5+ Years Employment Type: Full-Time About Okta Okta is The World s Identity Company. We empower people to securely use any technology, anywhere, on any device. Through our Okta and Auth0 platforms, we provide secure access, authentication, and automation placing identity at the center of security and growth for thousands of organizations. We value diverse perspectives and lifelong learners. We re not looking for someone who checks every box we re looking for someone who will make us better with their unique experiences. Team: Business Technology Data Engineering The Data Engineering team at Okta supports cross-functional partners by building scalable, secure, and high-performing platforms. These platforms power decision-making and business processes across sales, marketing, engineering, finance, product, and operations. As part of this team, you ll contribute to data solutions that fuel Okta s hyper-growth. You will have the opportunity to work with cutting-edge technologies in cloud infrastructure, data lakes, automation, and CI/CD pipelines. The Role: Senior Data Engineer As a Senior Data Engineer, you will design, build, and manage modern data pipelines, infrastructure, and automation frameworks. You ll help scale our enterprise data platform using tools such as Snowflake, dbt, Airflow, Databricks, and AWS, while ensuring security, observability, and performance. You ll also contribute to CI/CD pipelines, infrastructure as code (IaC), and secure development lifecycle practices, enabling consistent, efficient, and secure delivery of data solutions. Key Responsibilities Platform Development & Infrastructure Design and maintain scalable data pipelines and platforms using Snowflake, AWS, Databricks, dbt, and Airflow. Manage infrastructure with Terraform, enabling repeatable and consistent deployments. Develop and maintain robust CI/CD pipelines using GitHub Actions, GitLab, or Jenkins. Containerize data services using Docker for better scalability and portability. Security & Compliance Implement and enforce secure development lifecycle practices, integrating tools like DAST, SAST, SCA, and Secret Scanning into pipelines. Conduct vulnerability scanning and apply patches to ensure system integrity. Ensure data security and compliance with industry standards and regulations. Collaboration & Innovation Collaborate with data engineers, data scientists, and analysts across business units to ensure data availability and integrity. Identify opportunities for automation and optimization within the data platform. Stay updated on emerging technologies and drive adoption of best practices. Must-Have Skills Bachelor s degree in Computer Science, Engineering, or a related technical field. 5+ years of experience in data engineering, including: Advanced SQL and ETL development with Airflow and dbt. Experience with data warehouses such as Snowflake, Redshift, or BigQuery. Strong hands-on experience with AWS (S3, Lambda, EC2, EMR, EKS). 2+ years of experience managing CI/CD pipelines using tools like GitHub Actions, GitLab, Jenkins, or ArgoCD. Experience with Terraform and Docker. Proficiency in backend languages such as Python, Java, or Go. Preferred Skills Experience with lakehouse architectures like Databricks, including knowledge of Delta Lake and Apache Iceberg. Background in infrastructure security, vulnerability management, and observability tooling. High Impact: Help build and scale the data platform that powers Okta s global business. Cutting-Edge Stack: Work with best-in-class technologies like AWS, Snowflake, dbt, Terraform, and Databricks. Collaborative Culture: Join a diverse, inclusive, and globally distributed team that values knowledge sharing and continuous learning. Career Growth: Shape the future of Okta s data engineering practice while expanding your technical and leadership skills. Bring your passion for data, cloud, and automation and let s shape the future of secure, scalable enterprise data platforms together. Qualification : Bachelors degree in Computer Science, Engineering, or a related technical field

Position Title: Data Architect Department: R&D Engineering Location: Bangalore Experience: 15+ Years Industry: SaaS / Conversational Engagement / Customer Experience Technology About Acqueon: Acqueon is a leading provider of conversational engagement software that enables customer-centric enterprises to proactively engage with their customers across voice, messaging, and email channels. By leveraging a powerful data platform, predictive models, and intelligent workflows, we help brands enhance customer experience, improve collections, and drive revenue growth. With over 200 global clients, Acqueon is at the forefront of AI-powered customer engagement. Role Overview: We are seeking a visionary and technically hands-on Data Architect to lead the development of enterprise-scale data platforms and engineering solutions. You will work closely with Product Owners, Engineering Leadership, and cross-functional teams to define and execute a strategic technology roadmap aligned with Acqueon s business goals. As a key member of our R&D team, you ll lead the design and development of highly scalable, low-latency, fault-tolerant data systems, while mentoring top-tier engineering talent and driving high-impact product features. Key Responsibilities: Architect & Lead: Design and lead development of scalable data architectures and solutions supporting real-time and batch processing, analytics, and enterprise applications. Strategic Ownership: Define and implement the data strategy, technology roadmap, and long-term architecture vision for Acqueon s platforms. Leadership: Manage and mentor a team of senior developers and engineers, fostering innovation, ownership, and delivery excellence. Cross-functional Collaboration: Work with Product, Sales, Engineering, and Customer teams to align on feature development and delivery strategy. Project Management: Oversee the end-to-end delivery of complex features, ensuring adherence to timelines, scalability, and quality standards. System Design: Review architecture and design for robustness, performance, and fault tolerance, including multi-region, high-availability setups. R&D Enablement: Collaborate with international R&D teams and align development efforts across global product initiatives. Innovation & Optimization: Drive architectural decisions, recommend performance improvements, and ensure best practices for enterprise-scale data solutions. Required Skills & Experience: Education: Bachelor s or Master s in Computer Science, IT, or related field. Experience: 15+ years in software development and data architecture, with leadership experience in managing engineering teams. Architecture Expertise: Proven experience in designing scalable, concurrent, distributed, and highly available data systems. Database Proficiency: Strong in SQL/NoSQL databases Experience with MS SQL, Aerospike, DynamoDB, Snowflake In-depth knowledge of micro-partitions, cluster keys, warehouse cloning, time travel in Snowflake Strong in writing and tuning complex stored procedures ETL & Pipelines: Experience in building ETL pipelines and integrating data from S3, Kinesis Streams, APIs Cloud & DevOps: Strong understanding of Docker, AWS, and cloud-native deployment architectures Setting up multi-region resilience, disaster recovery strategies Technologies: Elasticsearch, AWS data services, container orchestration Big Data & Analytics: Exposure to analytical processing and statistical modeling is a plus Leadership: Strong project management skills, stakeholder engagement, and team mentoring experience Preferred Qualifications: Background in customer engagement, VDI, Cybersecurity, or Secure Access technologies Previous experience working with distributed R&D and product teams Knowledge of Acqueon, Citrix, VMware, Omnissa platforms is a plus Certifications in AWS, Snowflake, or similar technologies are an advantage Soft Skills & Behavioral Traits: Strong verbal and written communication skills Strategic thinking with hands-on execution ability High accountability and ownership mindset Ability to work in a fast-paced, dynamic, startup-like environment Comfortable with ambiguity and context-switching Team player with the ability to lead by influence and collaboration Be a part of a fast-growing, AI-driven SaaS company disrupting the customer engagement space Work on cutting-edge technologies with global product teams Ownership of end-to-end solutions and ability to shape the data platform of the future A culture that promotes innovation, agility, and career growth

Position: Manager - Analytics Location: SEZ4, Bangalore, Karnataka, India Department: Advanced Analytics Employment Type: Subexian Experience Required: 6 to 9 years Job Overview: We are seeking an experienced Manager - Analytics to lead a team of talented data scientists in delivering impactful data-driven solutions. The ideal candidate will have a solid background in analytical methodologies, including machine learning, statistical modeling, and business analytics. You ll be responsible for collaborating with business stakeholders, driving the design and development of advanced analytics models, and ensuring the delivery of high-quality insights that support strategic decision-making. Key Responsibilities: Analytical Methodology: Research, evaluate, and implement new analytical methodologies and approaches to build innovative data-driven solutions. Utilize a blend of mathematics, statistics, machine learning, and business knowledge to solve complex problems. Business Collaboration: Work closely with business leaders and data owners to define key problems and challenges, ensuring the solutions developed have a significant impact on the business. Team Leadership: Lead and mentor a team of junior data scientists, guiding them through the development, deployment, and refinement of machine learning models in a production setting. Advanced Modeling: Utilize a wide range of analytical models, including reliability models, Markov models, stochastic models, Bayesian modeling, classification models, neural networks, and more to address business challenges effectively. Hands-On Expertise: Apply strong hands-on skills in R and Python, using libraries such as NLTK and Sklearn for developing machine learning models and data analysis. Large Data Management: Work with large datasets and distributed computing frameworks like MapReduce, Hadoop, and Hive, ensuring scalable and efficient data processing. Continuous Improvement: Stay up to date with the latest advancements in analytics and machine learning, continually enhancing models and methodologies to deliver cutting-edge insights. Required Technical Skills: Hands-on Experience in Python & R: Strong proficiency in R and Python programming, with experience in libraries such as NLTK, Sklearn, and other machine learning frameworks. Advanced Statistical & Machine Learning Techniques: Proven expertise in at least one of the following: Reliability models Markov Models Stochastic models Bayesian Modelling Classification Models Cluster Analysis Neural Networks NLP (Natural Language Processing) Deep Learning Non-parametric Methods Multivariate Statistics Big Data Tools: Experience working with large datasets and distributed computing platforms such as MapReduce, Hadoop, Hive, etc. Soft Skills: Leadership & Collaboration: Strong leadership skills with the ability to mentor a team of junior data scientists. Excellent collaboration and communication skills to work with business and technical teams. Problem-Solving & Critical Thinking: Ability to approach complex business problems analytically and come up with data-driven solutions. Continuous Learning: A passion for staying up to date with the latest trends and advancements in analytics, machine learning, and data science. At Subex, you ll have the opportunity to work on cutting-edge projects that make a tangible impact on the business. If you're passionate about leading analytics teams and leveraging data science to drive business success, we would love to have you on board.