Hadoop Jobs in Bengaluru

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

Data Engineering Lead Bengaluru | Engineering | Full-Time About Fam (formerly FamPay) Fam is India s first payments app designed for everyone aged 11 and above. FamApp enables seamless online and offline payments through UPI and FamCard. Our mission is to empower over **250 million young Indians** to start their financial journey early, becoming financially aware and confident. Founded in 2019 by IIT Roorkee alumni, Fam is backed by top-tier investors including Elevation Capital, Y-Combinator, Peak XV (Sequoia Capital India), Venture Highway, and angels like Kunal Shah and Amrish Rao. About the Role We re looking for a visionary **Data Engineering Lead** to take **end-to-end ownership** of Fam s data ecosystem from data ingestion and storage to processing and delivering actionable insights. You ll **define the data strategy and architecture** that supports both batch and **real-time** use cases, ensuring scalability, reliability, and governance across the organization. You will be instrumental in enabling accurate, complete, and trusted data flow that powers business intelligence, analytics, and product decision-making. This role involves **leadership, strategic thinking**, and hands-on problem solving. What You ll Do Own the full data lifecycle: ingestion, organization, storage, processing, and presentation. Define and execute **data architecture and strategy** aligned with operational and analytical goals. Build **scalable, reliable, and observable data systems** supporting batch and near real-time processing. Ensure **data quality, governance, and compliance**, proactively resolving discrepancies. Collaborate with product, engineering, and business teams to define, track, and optimize key metrics. Anticipate data-related challenges and implement preventive solutions. Lead, mentor, and grow the data engineering team, fostering innovation and accountability. Must-Haves 10+ years experience in data engineering, including proven leadership of teams or projects. Expertise designing, building, and scaling end-to-end data pipelines and systems. Deep understanding of the data lifecycle, from ingestion through business reporting. Strong communication skills and ability to collaborate across technical and business teams. Solid knowledge of **data governance, quality assurance, and compliance standards**. Experience with observability and proactive monitoring for data systems. Proficiency in Python and SQL; familiarity with Scala or Java. Hands-on experience with streaming and batch data frameworks. Experience designing large-scale data lakes and warehouses with best practices for schema evolution and partitioning. Strong background with **cloud platforms (AWS, GCP, or Azure)**. Fintech or regulated industry experience is a plus. Good to Have Fintech-specific data experience, including regulatory compliance and reporting. Deployment experience with **real-time analytics** and event-driven architectures. Familiarity with containerization and infrastructure tools like Docker, Kubernetes, Terraform. Knowledge of data observability tools (Monte Carlo, Databand, etc.). Exposure to **ML pipelines** and model deployment. Solve challenging problems at the intersection of big data, real-time processing, and fintech. Lead impactful data initiatives at a rapidly growing startup. Collaborate with a world-class team of engineers, data scientists, and product leaders. Competitive compensation, equity, and benefits. Clear career growth opportunities in leadership and innovation. Perks That Go Beyond the Paycheck Relocation assistance for a smooth move. Free office meals (lunch & dinner). Generous leave policies (birthday, period, parental support, and more). Salary advances and loan policies for financial support. Quarterly rewards, recognition, and referral incentives. Access to the latest gadgets and tools. Comprehensive health insurance with mental health support. Tax benefits like food coupons, phone allowances, and leasing options. Retirement benefits including PF contribution, leave encashment, and gratuity. About FamApp FamApp focuses on financial inclusion for the next generation by offering UPI and card payments to users aged 11+. Our flagship product, FamX, integrates UPI and card payments seamlessly, helping users manage, save, and learn about their finances effortlessly. With over **10 million users**, FamApp is revolutionizing how young Indians transact eliminating the need to carry cash and offering customizable FamX cards with personal doodles for a fun, unique payment experience. Join Our Dynamic Team At Fam, we foster a people-first culture with flexible work schedules, generous leave, comprehensive health benefits, and mental health support. You ll be part of a passionate, talented, and fun team shaping the future of fintech for India s youth.

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: 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!

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.

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

Lead Data Engineer | ThoughtWorks | Bangalore, India Location: Bangalore, India Employment Type: Full-time, Regular Industry: Information Technology About ThoughtWorks At ThoughtWorks, we're a global technology consultancy that integrates strategy, design, and engineering to drive digital innovation. For over 30 years, we've worked alongside our clients to deliver solutions that challenge the status status quo. With a diverse and inclusive team, we empower each other to grow through shared learning, fostering an environment where innovation thrives. Our commitment to a cultivation culture is key to our success, and we re looking for a Lead Data Engineer to join our Bangalore team and lead transformative projects. Job Overview As a Lead Data Engineer at ThoughtWorks, you will be responsible for designing, developing, and operating modern data architectures that meet client business objectives. You will lead and manage data engineering projects end-to-end, from strategic planning to hands-on coding, ensuring the delivery of scalable and efficient data solutions. Working with cutting-edge technologies, you ll collaborate with stakeholders, clients, and cross-functional teams to implement data-driven strategies that address complex business challenges. Key Responsibilities Project Leadership: Lead and manage data engineering projects from inception to completion, including goal-setting, scope definition, and ensuring on-time delivery in collaboration with cross-functional teams. Data Architecture & Solution Design: Collaborate with clients to design modern data architecture and implement end-to-end solutions that meet key business objectives. Create intricate data processing pipelines to address complex business problems. Stakeholder Collaboration: Work closely with stakeholders to understand business objectives and identify opportunities to leverage data and data quality improvements. Data Modeling & Governance: Develop data models using modern modeling techniques and implement them using appropriate technologies. Ensure compliance with data governance, security, and privacy requirements. Scalable Implementations: Partner with data scientists to design scalable implementations of their models, ensuring the solutions are robust and efficient. Clean, Iterative Code: Write clean, modular code based on TDD (Test-Driven Development) and implement continuous delivery practices to support and operate data pipelines. Technology Guidance: Advise clients on distributed storage and computing technologies, selecting the best options to fit their business needs. Data Quality Strategy: Define and incorporate data quality strategies into daily work processes to ensure high standards and compliance. Job Qualifications Technical Skills: Proven experience in data engineering and system design, with a focus on building Big Data architecture and data pipelines within distributed systems. Deep knowledge of data modeling and hands-on experience with modern data engineering tools and platforms. Strong programming skills, with expertise in building scalable, high-quality data pipelines using languages like Python, Java, Scala, or others. Experience with distributed storage platforms (e.g., Hadoop, Amazon S3, etc.) and distributed processing platforms (e.g., Spark, Flink). Experience working with SQL, NoSQL, data lakes, and other data storage technologies. Familiarity with data visualization techniques and ability to communicate insights effectively across varying audiences. Professional Skills: Stakeholder Management: Strong ability to liaise between clients and other key stakeholders, ensuring trust and buy-in throughout projects. Adaptability & Resilience: Comfortable handling ambiguity and finding innovative solutions to complex challenges. Leadership & Mentorship: Experienced in coaching and mentoring team members, fostering a culture of professional growth and accountability. Risk & Conflict Management: Skilled in managing risks and resolving conflicts, driving projects forward despite challenges. Relationship Building: Natural at cultivating strong relationships with clients, stakeholders, and internal teams to create new opportunities. What You Bring to the Team Leadership: A proven track record in leading high-performance teams and supporting colleagues in their professional development. Curiosity & Innovation: A passion for data and technology and a willingness to continually learn and push the boundaries of what's possible. Collaboration: Ability to work closely with cross-functional teams and stakeholders to design and implement innovative data solutions. At ThoughtWorks, we believe in giving you the autonomy to carve out your unique career path, while providing support through development programs and a vibrant culture of learning. You ll work on exciting projects with a diverse team, solve complex challenges, and make an impact at a global scale. Join ThoughtWorks and be part of a global community of innovators. Together, we turn curiosity into action and creativity into impactful solutions.

Sr. Data Engineer - AWS - Big Data Location:Bangalore Type of Employment: Full-Time Experience Required: 7 to 10 years Job Overview: We are seeking a highly skilled Sr. Data Engineer with expertise in AWS cloud technologies and Big Data to join our Cloud Data Architect Team at Infocepts. In this critical role, you will design and implement robust data solutions using technologies like EMR, Athena, PySpark, AWS Lambda, S3, and other AWS services. The ideal candidate will have a strong foundation in database concepts and SQL and will be responsible for building scalable data pipelines to support high-performance data processing. Key Responsibilities: Technology Assessment and Design: Study the existing technology landscape and evaluate current data integration frameworks. Assist in designing complex Big Data use cases leveraging AWS services. Documentation and Stakeholder Communication: Prepare and maintain comprehensive project documentation, adhering to quality guidelines and schedules. Work closely with Architects and Project Managers to provide accurate estimations, scoping, and scheduling assistance. Clearly communicate design decisions and conduct Proof-of-Concepts to validate new solutions before implementation. Process Improvement and Automation: Identify areas for process automation to improve efficiency and team productivity. Provide expert guidance and troubleshooting support to junior Data Engineers. Training and Knowledge Sharing: Develop and deliver technology-focused training sessions for the team, ensuring continuous knowledge sharing. Share expertise through Expert Knowledge Sharing sessions with Client Stakeholders. Essential Skills: AWS Services Expertise: In-depth knowledge of S3, EC2, EMR, Athena, AWS Glue, and Lambda. Big Data Technologies: Proficiency with Apache Spark, Databricks, and Big Data table formats such as Delta Lake (open-source). Data Warehousing: Strong understanding of data warehousing concepts and architectures. Programming Skills: Advanced programming skills in Python for building data pipelines. SQL Expertise: Strong SQL skills for data transformation, aggregation, and querying large datasets. ETL Workflow Development: Expertise in creating ETL workflows with complex transformations (e.g., SCD, deduplication, aggregation). Orchestration Tools: Familiarity with orchestration tools like Apache Airflow. MPP Databases: Experience with at least one MPP database (e.g., AWS Redshift, Snowflake, SingleStore). Cloud Databases: Exposure to cloud databases like Snowflake or AWS Aurora. Desirable Skills: Cloud Databases: Familiarity with Snowflake, AWS Aurora. Big Data Technologies: Experience with Hadoop and Hive. AWS Certification: Associate or Professional Level AWS Certification. Advanced Knowledge of Big Data Solutions: Exposure to big data tools and frameworks on cloud platforms. Qualifications: Experience: 7+ years of overall IT experience, with 5+ years specifically focused on AWS-related projects. Educational Background: Bachelor's degree in Computer Science, Engineering, or a related field (Master's degree is a plus). Technical Certifications: Demonstrated commitment to continuous learning through certifications or relevant training. Qualities: Strong analytical and problem-solving skills to deep dive into complex technical challenges.

Position: Cloud Data Engineer AWS Big Data Location: Bangalore, India Employment Type: Full-time Experience Required: 5 to 8 years Purpose of the Position: Join the Infocepts Cloud Data Architect Team as a Cloud Data Engineer and help design and implement cutting-edge big data solutions on AWS. You will leverage your expertise in EMR, Athena, PySpark, S3, AWS Lambda, and SQL to develop robust and scalable data platforms. Key Responsibilities: Technology Assessment and Design: Assess existing technology landscape and data integration frameworks. Design complex Big Data use cases using AWS services under guidance of the Architect. Support architectural decision-making by evaluating trade-offs in cost, performance, and durability. Recommend optimizations to existing data infrastructure. Documentation and Stakeholder Communication: Create project documentation adhering to quality and delivery standards. Collaborate closely with Architects and Project Managers for scoping, estimation, and planning. Present design decisions to technical and business stakeholders clearly. Conduct PoCs and design review sessions. Process Improvement and Automation: Identify and suggest opportunities for automation and process enhancements. Mentor junior engineers and support technical problem solving. Training and Knowledge Sharing: Prepare and deliver internal training on AWS and Big Data topics. Lead client knowledge sharing sessions and contribute to case studies. Essential Skills: In-depth experience with AWS services: S3, EC2, EMR, Athena, Glue, Lambda Familiarity with MPP databases like Redshift, Snowflake, or SingleStore Proficiency in Apache Spark and Databricks Strong programming skills in Python Experience building data pipelines using AWS and Databricks Knowledge of Big Data file formats such as Delta Lake Advanced SQL skills for large-scale data manipulation Hands-on experience with Apache Airflow or similar orchestration tools Strong understanding of ETL workflows and data warehousing concepts Desirable Skills: Cloud databases: AWS Aurora, Snowflake Experience with Hadoop and Hive AWS Certifications (Associate or Professional level) are a plus Qualifications: Bachelor s degree in Computer Science, Engineering, or related field (Master s preferred) Overall 5+ years of IT experience with at least 3 years in AWS Big Data projects Ongoing learning and technical certifications are strongly encouraged Key Qualities: Strong problem-solving and analytical thinking Self-driven with a passion for emerging data technologies Excellent communication and client presentation skills Ability to work in cross-functional, agile teams Apply now to be part of a high-impact data transformation team working on large-scale cloud data projects! Qualification : Bachelors degree in Computer Science, Engineering, or related field (Masters preferred)

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/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.

Intuit is a global leader in financial technology, dedicated to helping individuals and businesses thrive. Our suite of products, including TurboTax, Credit Karma, QuickBooks, and Mailchimp, serves approximately 100 million customers worldwide. At Intuit, we believe in providing everyone with the tools and resources they need to achieve financial success. We are constantly innovating to make financial empowerment a reality for all. Job Overview Join the Intuit Data Platform (IDP) team as a Staff Engineer and help us transform the way we handle big data! The IDP team is responsible for the Intuit Analytics Platform, which powers real-time data ingestion, cataloging, analytics, and machine learning across the entire organization. As Intuit s customer base grows, so does the volume of data we process. Our engineering excellence ensures that we can scale and leverage this data to drive machine learning and product innovations. We re in the process of building the next-generation real-time and batch ingestion engine, capable of indexing, cataloging, and organizing data and metadata. We are passionate about using open-source technologies to solve challenges and contributing back to the community. If you're excited about building a platform that will directly impact data scientists and analysts and have a desire to shape the future of data at Intuit, then come join us! Key Responsibilities Architect & Design: Build fault-tolerant and scalable big-data platforms using open-source technologies to handle massive datasets. Data Solutions: Create architecture solutions that address complex use cases like data normalization, lineage, governance, ontology, and discoverability. Cross-Team Collaboration: Work with analysts and data scientists to understand data requirements for building operational propensity models and gaining deep customer insights. Hands-On Coding: Lead development efforts within the Hadoop ecosystem using technologies such as Java MapReduce, Spark, Scala, HBase, and Hive to build and optimize data pipelines for both real-time and batch applications. Database Management: Work with NoSQL, SQL, and in-memory databases to design high-performance data systems. Code Reviews: Ensure code quality, consistency, and adherence to best practices through regular code reviews. Architectural Alignment: Ensure alignment between enterprise architecture and business requirements. Prove Feasibility: Conduct proof-of-concept (POC) experiments for new technologies or approaches and drive them to production. Collaboration with Data Cataloging Team: Work closely with data catalog teams and architects to index and catalog all data sources at Intuit. Agile Leadership: Lead fast-paced development teams using agile methodologies and promote best practices in software development, testing, and incident response. Design & Model: Build dimension models suited for customer business use cases and ensure seamless integration of business and technical requirements. Qualifications Experience: 12+ years of relevant experience, with at least 5+ years specializing in the big data domain. Big Data Architecture: Proven experience in architecting end-to-end ecosystems for big data and analytics platforms. Expert Knowledge: Deep expertise in building fault-tolerant, scalable big data solutions, especially using the Hadoop ecosystem (Hive, HBase, Spark, Kafka, MapReduce, etc.). Programming Expertise: Mastery of Java and Scala, with a focus on building high-throughput data services. Machine Learning: Knowledge of machine learning principles and AI applications in big data. Big-Data Technologies: Familiarity with tools such as HDFS, Storm, Zookeeper, Cassandra, Redshift, GraphDB, and others. Understanding both real-time and batch processing in the Hadoop ecosystem. Communication: Strong communication skills, with an ability to explain complex technical topics to both technical and non-technical audiences. Programming Skills: Intermediate experience in Python or R for data processing. Education: BE/BTech/MS in Computer Science or a related field (or equivalent experience). Collaboration: Demonstrated ability to work cross-functionally and lead change through influence and example. At Intuit, you ll be part of a talented, passionate team working on innovative solutions that shape the future of data analytics and machine learning. As a Staff Engineer, you ll have the chance to work with cutting-edge technologies, build scalable systems, and help revolutionize how Intuit leverages data to drive product innovation. If you're looking for a dynamic environment where you can have a meaningful impact, come join us at Intuit! Qualification : BE/BTech/MS in Computer Science (or equivalent)

Data Engineer Role Overview We are looking for a Data Engineer to design, develop, and maintain scalable data pipelines and ETL processes. You will work closely with data scientists, analysts, and engineers to ensure efficient data processing and storage solutions that support business intelligence and analytics needs. This role requires expertise in SQL, big data technologies, and cloud platforms to build and optimize data workflows. Key Responsibilities Data Pipeline Development & Optimization Design and build scalable ETL/ELT processes for structured and unstructured data. Develop and maintain data ingestion frameworks to handle large datasets efficiently. Ensure data integrity, consistency, and security across multiple sources. Database & Data Warehouse Management Develop, optimize, and maintain relational and NoSQL databases. Implement data modeling best practices for performance and scalability. Work with cloud-based data warehouses (e.g., Snowflake, Redshift, BigQuery). Big Data & Cloud Technologies Leverage big data tools (e.g., Spark, Hadoop, Databricks) for data processing. Work with cloud platforms (e.g., AWS, Azure, GCP) to build and optimize data solutions. Develop real-time and batch processing workflows. Collaboration & Documentation Work closely with data scientists, engineers, and business teams to understand data requirements. Document data pipelines, architecture, and workflows for scalability and maintenance. Required Qualifications & Skills Technical Expertise: Strong experience with SQL and Python for data processing. Proficiency in ETL/ELT frameworks and data integration techniques. Hands-on experience with big data tools (e.g., Apache Spark, Hadoop, Kafka). Cloud & Database Management: Expertise in cloud data platforms (Azure, AWS, GCP). Experience with data warehousing solutions (Snowflake, Redshift, BigQuery). Understanding of data governance, security, and compliance. Performance Optimization & Troubleshooting: Ability to optimize SQL queries and improve data processing efficiency. Experience troubleshooting complex data pipeline issues. Apply Now & Be Part of an Innovative Data Team!

Data Scientist Role Overview We are looking for a Data Scientist with a strong foundation in Python, hands-on experience with machine learning techniques, and excellent communication skills. The ideal candidate will work on data-driven solutions, develop predictive models, and collaborate with cross-functional teams to translate business challenges into actionable insights. Key Responsibilities Data Analysis & Modeling Conduct in-depth data analysis to identify trends and patterns. Develop and implement predictive models using ML algorithms (regression, classification, clustering, decision trees, neural networks). Utilize statistical techniques to derive insights and drive business decisions. Data Pipeline & Deployment Build and deploy ETL pipelines to extract, transform, and load data from multiple sources. Optimize machine learning models for efficiency and scalability. Collaboration & Communication Work closely with business stakeholders, engineers, and analysts to understand challenges and propose data-driven solutions. Effectively communicate complex technical concepts to both technical and non-technical audiences. Present findings using data visualization tools. Continuous Learning & Innovation Stay updated on the latest advancements in ML, AI, and data science. Contribute to the development and improvement of the data science infrastructure. Required Skills & Qualifications Technical Expertise: Strong proficiency in Python (pandas, NumPy, scikit-learn, TensorFlow/PyTorch). Experience with ML techniques (regression, classification, clustering). Solid understanding of statistical concepts and data analysis methodologies. Experience with data visualization and presentation tools. Soft Skills & Communication: Strong problem-solving and critical-thinking abilities. Excellent communication and interpersonal skills. Ability to work independently and in teams. Educational Background: Bachelor's degree in Computer Science, Statistics, Mathematics, or a related field. Preferred Skills (Nice to Have) Experience with cloud computing platforms (AWS, Azure, GCP). Exposure to big data technologies (Hadoop, Spark). Proficiency in data visualization tools (Tableau, Power BI). Master s degree in a relevant field. Apply Now & Be Part of an Innovative Data Science Team! Qualification : Bachelor's degree in Computer Science, Statistics, Mathematics, or a related field.

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.

Job/Position Summary 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

Data Engineer Location: Bangalore Company: Capital One India About Capital One At Capital One, we're redefining how technology solves real-world financial challenges. As a technology-driven company, we bring together talented engineers, data scientists, and designers to innovate at scale and deliver meaningful impact to millions of customers. If you're passionate about building powerful data solutions, exploring cutting-edge technologies, and working in a collaborative, fast-paced environment this is the place for you. About the Role As a Data Engineer at Capital One, you ll join a team of innovators who design and build next-generation data platforms and pipelines that power real-time decision-making. You ll collaborate across disciplines engineering, product, machine learning, and cloud infrastructure to transform how we leverage data at scale. What You ll Do Collaborate across Agile teams to design, develop, test, and deploy data-driven solutions. Build and support scalable data pipelines using modern data engineering tools and cloud services. Work on real-time and batch data processing systems that integrate with distributed microservices and ML platforms. Use programming languages such as Python, Java, or Scala with SQL, NoSQL, and cloud data warehouses like Redshift or Snowflake. Contribute to code reviews, unit testing, and performance optimization to ensure high-quality data systems. Partner with product managers and platform teams to deliver robust, cloud-native data solutions that power business decisions. Stay ahead of tech trends, share knowledge, and mentor junior engineers. Basic Qualifications Bachelor s degree in Computer Science, Engineering, or a related field. 1.5+ years of hands-on experience in application or data engineering (excluding internships). At least 1 year of experience working with big data technologies. Preferred Qualifications 3+ years of application/data engineering experience using Python, Scala, Java, or SQL. 1+ year of experience with cloud platforms (AWS, Azure, or GCP). 2+ years of experience with distributed computing tools (Spark, Hadoop, Hive, EMR, Kafka, etc.). 1+ year working on real-time streaming applications. 1+ year of experience with NoSQL databases (MongoDB, Cassandra). 1+ year of experience with data warehousing (Redshift, Snowflake). 2+ years working with Linux/Unix systems and shell scripting. Familiarity with Agile methodologies and modern DevOps practices. Why Join Capital One Work on high-impact data solutions at one of the world s most innovative financial institutions. Be part of a collaborative tech culture that values experimentation and learning. Access to top-tier tools, mentorship, and career development opportunities. Competitive compensation and benefits in a mission-driven environment. Qualification : Bachelors degree in Computer Science, Engineering, or a related 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