Data Pipeline Design Jobs in Bengaluru

Lead Software Engineer - Scale & Performance Location: Bengaluru Experience: 6 12 years About VuNet VuNet is a pioneer in Business Journey Observability, using Big Data and Machine Learning to revolutionize digital experiences in the financial services industry. Our platform delivers end-to-end visibility into customer journeys, helping organizations proactively resolve issues, ensure operational resilience, and deliver superior user satisfaction. With over 28 billion digital transactions monitored every month and serving more than 300 million users globally, VuNet is shaping the future of observability for some of the largest banks and financial institutions. We are Series B funded, part of NASSCOM s DeepTech Club, and recognized by global analysts such as Gartner and Omdia. Your Role: Lead Software Engineer - Scale & Performance As a Lead Software Engineer for Scale & Performance, you ll own the performance and scalability benchmarks for VuNet s observability platform. You will work with cutting-edge technologies, design robust test frameworks, and ensure that our platform scales seamlessly to meet the demands of millions of users. Roles & Responsibilities Own performance and scalability benchmarking for key platform components (ingestion pipelines, data storage, and query services). Design and execute load, stress, soak, and capacity tests across microservices, agents, and ingestion layers. Identify and resolve performance bottlenecks in both infrastructure (CPU/memory/IO) and application layers (API latency, throughput, GC behavior). Develop and maintain performance test frameworks, preferably using Kubernetes-based environments. Collaborate with DevOps and SRE teams to optimize system configurations (Kubernetes, Postgres/TimescaleDB, ClickHouse, Kafka) for scale. Implement OpenTelemetry for service instrumentation to monitor system health and latency (p50/p95/p99 metrics). Contribute to capacity planning, scaling strategies (horizontal/vertical), and resource optimization. Analyze production incidents related to scaling issues and drive permanent fixes. Work with engineering teams to design scalable architecture patterns and define SLIs/SLOs for system performance. Document performance baselines, tuning guides, and scalability best practices for internal use. What You Bring Mandatory Skills: Strong background in performance engineering for large-scale distributed systems or SaaS platforms. Expertise in Kubernetes, container runtimes (containerd/Docker), and resource profiling in containerized environments. Solid understanding of Linux internals, CPU/memory profiling, and network stack tuning. Hands-on experience with observability tools (Prometheus, Grafana, OpenTelemetry, Jaeger, Loki, Tempo, etc.). Familiarity with observability platform datastores like ClickHouse, PostgreSQL/TimescaleDB, Elasticsearch, or Cassandra. Experience with performance benchmarking tools such as k6, Locust, JMeter, or custom Golang/Python scripts. Ability to interpret system metrics (CPU usage, memory, GC, latency) and correlate across different layers. Nice-to-Have Skills: Experience with agent benchmarking (OpenTelemetry Collector, custom data shippers). Exposure to streaming systems like Kafka, NATS, or Pulsar. Familiarity with CI/CD pipelines for performance testing and regression tracking. Knowledge of cost optimization and capacity forecasting in cloud environments (AWS/GCP/Azure). Proficiency in Go, Python, or Bash scripting for automation and data analysis. Life at VuNet: At VuNet, we're building a world-class observability platform, and we re just getting started. You ll be part of a passionate, problem-solving team that embraces collaboration, fast learning, and staying ahead of emerging technologies like Gen AI. We foster a high-trust, inclusive culture where collaboration, ownership, and innovation are central to our success. If you're looking to work on cutting-edge tech, make a real impact, and grow with a supportive team you ll fit right in at VuNet. Benefits: Comprehensive health insurance coverage for you, your parents, and dependents. Mental wellness and 1:1 counseling support. A culture that promotes continuous learning, innovation, and career growth. Transparent, inclusive, and high-trust workplace. Opportunities for skill enhancement with training programs focused on new Gen AI technologies.

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

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: Snowflake Data Engineer Location: Remote/Hybrid | Bengaluru, IND What You'll Do: Design & Optimize Data Pipelines: Build and enhance data pipelines and workflows using Snowflake, Azure, and DBT for efficient data ingestion, transformation, and analytics. Boost Performance: Optimize query performance and data storage within Snowflake to ensure lightning-fast data processing and retrieval. Implement ETL/ELT: Design and implement robust ETL/ELT processes, fully leveraging Snowflake's powerful capabilities for data ingestion and transformation. Collaborate Cross-Functionally: Work closely with various teams to understand their data needs and deliver high-quality, scalable data solutions. Ensure Data Governance: Uphold stringent data security, compliance, and governance standards, including data privacy and regulatory requirements. What You'll Bring: Experience: 4-10 years in data engineering, with a minimum of 3 years directly with Snowflake. SQL Mastery: Expert-level proficiency in SQL, including advanced querying, performance tuning, and data modeling. Deep Snowflake Knowledge: In-depth understanding of Snowflake architecture, features, and best practices for optimization and data management. Data Warehousing: Strong grasp of data warehousing concepts and dimensional modeling. Microsoft Technologies: Familiarity with Microsoft SSIS, SSAS, and SSMS. IaC & CI/CD: Knowledge of Infrastructure as Code (IaC) tools like Terraform and experience with GitHub Actions for CI/CD. Workflow Orchestration: Experience with tools like Airflow for managing and automating data workflows. Problem-Solving & Communication: A proactive, positive attitude with excellent written and verbal communication skills. Education: Bachelor s degree in Computer Science, Information Systems, or a related field. Bonus Points If You Have: Migration Experience: Hands-on experience with SQL Server to Snowflake migrations, especially using Fivetran. DBT & Fivetran: Proficiency with the data build tool (dbt) for data transformation and Fivetran for data integration. Cloud Platforms: Knowledge of cloud platforms such as AWS, Azure, or GCP. Certifications: Relevant certifications like Snowflake SnowPro, AWS Certified Data Analytics, or Azure Data Engineer.

Position: Business Technology Data Engineer Location: Bengaluru, India (Hybrid 3 days onsite) Company: Samsara Technologies India Pvt. Ltd. About Samsara Samsara (NYSE: IOT) is a leader in the Connected Operations Cloud, enabling businesses across industries like transportation, logistics, manufacturing, and field services to harness IoT data for safety, efficiency, and sustainability improvements. Samsara helps organizations digitize physical operations at scale, improving outcomes that impact global infrastructure. Role Overview Samsara is seeking a Business Technology Data Engineer to join its Data & Analytics team within the Business Technology division. In this role, you will design, build, and optimize end-to-end data pipelines and infrastructure for various business-critical systems across CRM, marketing, support, and product platforms. You'll collaborate with teams across the company to build reliable and scalable data solutions that power reporting, automation, and analytics. This hybrid role requires working 3 days per week from the Bengaluru office and 2 days remotely, with working hours aligned to India Standard Time (IST). Key Responsibilities Data Engineering & Platform Development Design and maintain ETL/ELT pipelines that integrate and transform data across business systems. Build scalable data infrastructure to support advanced analytics and real-time reporting needs. Write Python and SQL scripts for data ingestion, transformation, and validation. Data Integration & Enablement Work with diverse data sources: CRM, product telemetry, marketing automation, support ticketing, and order flow systems. Develop and support data lake and data warehouse solutions using Snowflake, Redshift, Databricks, or BigQuery. Ensure interoperability between applications and data layers. Performance & Quality Monitor and optimize pipeline performance, implement observability and alerting. Improve data quality, lineage, and governance across systems. Partner with internal stakeholders (e.g., Sales Ops, Marketing Ops, Analytics) to deliver reliable data products. Minimum Qualifications Bachelor s degree in Computer Science, Data Engineering, or related field. 5+ years of professional experience in data engineering. 3+ years experience building and maintaining end-to-end pipelines in a modern data stack. Strong in SQL and Python. Hands-on experience with: ETL tools: Fivetran, dbt Cloud: AWS (preferred), GCP, or Azure Databases: MySQL, PostgreSQL, Oracle, or similar Data Warehouses: Snowflake, Redshift, BigQuery, Databricks Preferred Qualifications Familiarity with API-based ingestion, serverless architecture (Lambda, API Gateway, SQS, etc.). Experience with monitoring tools (DataDog, CloudWatch, Splunk). Comfortable engaging stakeholders to translate business needs into data solutions. Proficiency in Docker, Kubernetes, or AWS Fargate is a plus. Qualification : Bachelors degree in Computer Science, Data Engineering, or related field

Job Title: Software Engineer C++ Location: Bengaluru Overview: We are seeking a highly capable and detail-oriented C++ Software Engineer to join our core development team in Bengaluru. This role requires strong expertise in C++ across both Windows and Linux environments, with a focus on performance optimization, multithreading, and scalable architecture design. The ideal candidate will have hands-on experience in high-throughput systems such as image processing pipelines or neural network-driven applications. Key Responsibilities: Develop and maintain high-performance C++ applications for Windows and Linux platforms. Optimize processing cycles and memory usage for large-scale image pipelines (e.g., 1 GB/sec camera data). Design and implement robust object-oriented software architectures emphasizing scalability and modularity. Work with multi-threaded programming libraries such as pThreads, OpenMP, and OpenCL. Translate, implement, and optimize DSP algorithms and/or neural network architectures. Build, maintain, and distribute DLLs and static libraries. Design and document API architectures for internal and external integrations. Utilize state machine architecture for structured process flow when required. Implement and maintain test frameworks to ensure code quality and performance. Follow best practices throughout the software development lifecycle, including code reviews and CI/CD. Maintain clear documentation and write clean, readable, and maintainable code. Required Skills & Experience: Proven C++ expertise on Windows and Linux platforms. Strong knowledge of object-oriented programming, design patterns, and modular code design. Experience with multi-threaded programming and parallel architecture design. Proficiency in API development and system integration. Experience building and managing shared and static libraries. Skilled in algorithm optimization, especially for image processing or neural network use cases. Familiarity with software lifecycle best practices, agile methodologies, and version control. Strong commitment to documentation and code quality. Preferred Qualifications: Exposure to state machine architecture. Experience with DSP or image processing algorithms. Understanding of test-driven development and CI frameworks.

Job Title: Engineering Manager Data Engineering Location: Bengaluru, Karnataka, India Department: Engineering Experience: 6 to 8 years Open Positions: 2 About the Role As an Engineering Manager - Data Engineering, you will lead a team of skilled data engineers who design, build, and maintain scalable data pipelines and infrastructure. You will collaborate with cross-functional teams and client stakeholders to deliver high-quality data systems that meet business goals. Your leadership will be pivotal in mentoring your team, driving project execution, and advancing data engineering capabilities across the organization. Key Responsibilities Lead, mentor, and develop a team of data engineers, fostering a collaborative and inclusive work environment. Conduct performance reviews, provide constructive feedback, and set clear goals for team members. Identify skill gaps and create opportunities for continuous professional growth. Plan, execute, and deliver data engineering projects on schedule and within scope. Coordinate with stakeholders to gather requirements, prioritize tasks, and define project timelines. Ensure all projects align with broader business objectives and data strategies. Oversee design, development, and maintenance of data pipelines, ETL processes, and data warehouses. Guarantee data quality, integrity, and security in all data engineering initiatives. Identify and drive process improvements to enhance efficiency and effectiveness in data operations. Manage client conversations to understand requirements and translate them into technical deliverables. Build and promote reusable frameworks to drive efficiency in data systems. Lead multiple projects involving streaming, batch, and large-scale data pipelines. Required Technical Skills Strong execution knowledge of data modeling, relational and non-relational databases (SQL and NoSQL). Expertise with ETL and orchestration tools such as IICS, Metatron, Airflow, Azure Data Factory, AWS Glue, or GCP Composer. Experience working with data warehouses like Snowflake, Redshift, Hive, or BigQuery. Proficiency in Apache Spark and optimization of Spark jobs. Strong programming skills in Python (mandatory), with knowledge of Scala, Rust, or Java as a plus. Understanding of Medallion architecture patterns. Advanced SQL skills with query optimization expertise. Experience with software development lifecycle, unit testing, and functional programming concepts. Required Non-Technical Skills Strong problem-solving skills with the ability to assess financial impacts of decisions. Excellent written and verbal communication skills, capable of engaging with mid-management client stakeholders. Ability to balance pragmatic solutions against perfect ones, driving team consensus and business value. Exceptional people management skills, including conflict resolution, empathy, negotiation, and active listening. Proven leadership and mentorship abilities, providing technical guidance to delivery teams. Self-driven, with a strong sense of ownership and accountability. Preferred Educational Qualifications Bachelor s degree in Engineering (B.E./B.Tech), MCA, or M.Sc. (Mathematics, Statistics). Lead and mentor a talented team working on cutting-edge data engineering projects. Collaborate closely with clients and cross-functional teams in a dynamic, fast-growing company. Drive innovation with scalable, high-impact data solutions. Grow your leadership and technical skills in a supportive, inclusive environment. Qualification : Bachelors degree in Engineering (B.E./B.Tech), MCA, or M.Sc. (Mathematics, Statistics).

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

Sr. Software Engineer, Search Relevance (Applied AI) Location: Bengaluru, India Company: Databricks Role Overview Join Databricks Applied AI team to develop and improve ML-powered search relevance systems. You will work on enhancing search ranking, query understanding, and building evaluation frameworks to enable scalable, seamless search experiences across millions of data assets on the platform. Key Responsibilities Develop and deploy ML/NLP-based relevance models integrated with Databricks products. Design automated pipelines for data preprocessing, query understanding, ranking, retrieval, and model evaluation. Collaborate with product managers and cross-functional teams to innovate in search and discovery features. Build robust frameworks for offline and online evaluation of search ranking improvements. BS or higher (MS/PhD preferred) in Computer Science or related fields. 6+ years of experience developing large-scale search relevance systems or impactful research. Experience applying Large Language Models (LLMs) to search relevance. Expertise in one or more of: query understanding, NLP, text mining, recommendations, personalization, discovery, conversational AI. Strong computer science fundamentals. Contributions to popular open-source projects a plus. Work with cutting-edge AI models and a world-class team to shape the future of AI-driven data products. Databricks powers data intelligence for thousands of organizations globally and fosters an environment of innovation and collaboration. Qualification : BS or higher (MS/PhD preferred) in Computer Science or related fields.

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.

Job Title: Senior Python Expert Experience: 3 to 8 years Overview of the Role: This role sets the benchmark for team software development processes and deployment procedures, while actively contributing to establishing best practices and methodologies within the team. Responsibilities: Develop backend services using Python Flask or similar web frameworks. Design and maintain data and pipeline management frameworks using open-source technologies such as Hadoop, Hive, Spark, HBase, Kafka Streaming, Tableau, Airflow, and cloud-based data engineering services like S3, Redshift, Athena, Kinesis. Design and develop efficient CRUD operations for large datasets with millions of records. Collaborate with teams to build and maintain innovative, reliable, secure, and cost-effective distributed solutions. Own and deliver complex application components within defined timelines. Ensure quality delivery using best practices in API development, performance, and scalability. Participate in customer communication, presentations, and resolution of critical issues. Contribute to architecture, feature set, and design decisions. Proactively recognize and address requirement inconsistencies and project risks. Break down work effectively and estimate accurately. Serve as a technical mentor and role model within the team. Required Skills: Strong knowledge of Python and a web framework like Flask. Experience with AWS services such as EC2, S3, Lambda, Step Functions, Glue, SNS, SQS, Secret Manager, and CodeBuild/CodePipeline. Solid understanding of SQL, including query writing, optimization, and database interaction tools. Experience with API development (RESTful services, Postman, API Gateway). Strong coding, debugging, and problem-solving skills. Understanding of architectural trade-offs and data engineering principles (data acquisition, ingestion, distributed processing, high availability). Ability to independently handle delivery of complex projects. Excellent team management and individual contributor skills. Good to Have Skills: Experience with Big Data frameworks like Hadoop and Spark. Knowledge of AWS Aurora. Familiarity with pip, setuptools, etc. Education: B.E./B.Tech, MCA, M.E./M.Tech.

Job Title: Sr. Engineering Manager - Data Engineering Level: L5 Experience: 13-16 years Overview We are seeking an experienced Engineering Manager with a strong background in Data Engineering, including ETL/ELT processes and cloud-based data platforms such as Snowflake. The ideal candidate will lead and mentor a team of data engineers, drive data architecture initiatives, and work closely with cross-functional stakeholders to ensure our data infrastructure supports evolving business needs. Key Responsibilities Team Leadership: Lead, mentor, and develop a high-performing data engineering team, fostering a culture of collaboration, innovation, and continuous learning. Data Pipeline Development: Oversee the design, development, and maintenance of robust ETL/ELT pipelines to ingest, transform, and process data at scale. Cloud Data Infrastructure: Drive the architecture and implementation of cloud-based data solutions, especially leveraging Snowflake, ensuring scalability, security, and reliability. Cross-Functional Collaboration: Partner with product managers, analysts, data scientists, and other business stakeholders to gather requirements and prioritize engineering efforts that deliver the most impact. Architecture and Design: Develop and enforce data architecture standards for high-performance data warehousing, ensuring seamless data integration across diverse sources. Performance Optimization: Identify and resolve performance bottlenecks, focusing on query optimization, cost management, and resource efficiency. Data Quality & Governance: Define and implement data quality frameworks and governance practices, ensuring data consistency and reliability across all pipelines. Innovation & Strategy: Stay informed on emerging data technologies and industry best practices, continuously improving processes and aligning solutions with long-term data strategies. Required Skills 8+ years of hands-on experience in data engineering, including 5+ years in a leadership role. Strong expertise in ETL/ELT processes and hands-on experience with tools like Talend, Informatica, or similar platforms. Deep proficiency in Snowflake or comparable cloud data platforms such as Redshift or BigQuery. Advanced SQL skills, including query optimization, performance tuning, data modeling, and schema design. Hands-on experience with Python or Java for data processing and automation. Knowledge of data governance, compliance standards, and data security best practices. Excellent communication and project management skills, with the ability to prioritize and manage multiple projects in parallel. Preferred Skills Exposure to Big Data technologies such as Spark, Hadoop, Databricks, Synapse, etc. Experience with workflow orchestration tools like Apache Airflow or AWS Step Functions. Familiarity with CI/CD pipelines and DevOps practices within data engineering. Experience working with BI tools like Tableau or Power BI, and reporting integrations.

Job Title: Data Engineer Location: Bengaluru (Hybrid) About Couchbase: As industries race to embrace AI, traditional database solutions fall short of rising demands for versatility, performance, and affordability. Couchbase is leading the way with Capella, the developer data platform for critical applications in our AI world. By uniting transactional, analytical, mobile, and AI workloads into a seamless, fully managed solution, Couchbase empowers developers and enterprises to build and scale applications with unmatched flexibility, performance, and cost-efficiency from cloud to edge. Trusted by over 30% of the Fortune 100, Couchbase is unlocking innovation, accelerating AI transformation, and redefining customer experiences. Come join our mission! Position Overview: We are seeking a highly skilled Data Engineer with a strong background in data warehousing, advanced analytics, and AI integration. The ideal candidate will have 5+ years of experience designing and implementing data pipelines, building robust analytics platforms, and working with modern data technologies like Snowflake, Google Cloud, Databricks, Looker, PowerBI, and Tableau. As part of our Delorean team, you will play a pivotal role in driving innovation and ensuring our data infrastructure supports strategic decision-making. Key Responsibilities: Data Infrastructure Development: Design, develop, and maintain scalable data pipelines and ETL processes to support data ingestion, transformation, and storage across multiple platforms. Experience with Cloud Data Platforms: Expertise in implementing and optimizing solutions using industry-leading tools such as Snowflake, Databricks, and Google Cloud Platform. Demonstrated ability to ensure high performance, scalability, and cost-effectiveness in data infrastructure and workflows. Analytics & Visualization: Build and maintain interactive dashboards and reports using Looker, PowerBI, and Tableau to provide actionable insights to business stakeholders. AI & Advanced Analytics: Collaborate with Data Science teams to integrate AI models and machine learning workflows into data pipelines for predictive analytics and automation. Data Governance: Ensure data quality, security, and compliance with industry best practices and regulatory requirements. Collaboration: Partner with cross-functional teams, including Product, Engineering, and Business Operations, to understand data requirements and deliver tailored solutions. Continuous Improvement: Identify opportunities to improve data workflows, adopt new technologies, and drive operational efficiency. Qualifications: Education: Bachelor s or Master s degree in Computer Science, Data Engineering, or a related field. Experience: 5+ years of hands-on experience in data engineering, data warehousing, or related fields. Technical Skills: Expertise in Snowflake, Databricks, and Google Cloud Platform (Mandatory experience in at least one tool). Proficiency in ETL/ELT processes and data pipeline tools (e.g., Apache Airflow, dbt). Experience with data visualization tools like Looker, Power BI, and Tableau. Strong SQL skills and familiarity with Python or Scala for data processing. Knowledge of AI/ML concepts and frameworks for integrating predictive models. Soft Skills: Excellent problem-solving skills with a proactive mindset. Strong communication and collaboration skills to work effectively with technical and non-technical teams. Ability to manage multiple priorities in a fast-paced environment. Modern customer experiences need a flexible cloud database platform that can power applications spanning from cloud to edge and everything in between. Couchbase s mission is to simplify how developers and architects develop, deploy, and consume modern applications. With Capella, our flexible, affordable cloud platform, we empower organizations to quickly build and deliver premium customer experiences with unmatched price-performance. More than 30% of the Fortune 100 trust Couchbase to power their modern applications. Benefits at Couchbase: Generous Time Off Program: Flexibility to care for yourself and your family. Wellness Benefits: Comprehensive medical plans, dental, vision, life insurance, and employee assistance programs. Financial Planning: RSU equity program, ESPP, retirement planning, and business travel insurance. Career Growth: A Be valued, Create value approach to your career development. Fun Perks: Ergonomic office setup, food & snacks for in-office employees, and more! Qualification : Bachelors or Masters degree in Computer Science, Data Engineering, or a related field.

Job Title: Senior Cloud Data Engineer Experience: 10+ Years Location: Bengaluru About Capgemini Invent: Capgemini Invent is the digital innovation, consulting, and transformation brand of the Capgemini Group. It brings together leading expertise in strategy, technology, data science, and creative design to help CxOs reimagine their businesses. We are a global business line dedicated to helping organizations envision and build what s next. Your Role: As a Senior Cloud Data Engineer at Capgemini Invent, you will design, develop, and maintain scalable data pipelines using advanced cloud technologies to ensure smooth data integration and efficient workflows. You will collaborate with cross-functional teams to deliver robust and optimized data solutions while ensuring compliance and security throughout the process. Key Responsibilities: Design, develop, and maintain scalable data pipelines using AWS services. Optimize data storage and retrieval processes to ensure efficiency and accessibility. Ensure data security and compliance with industry standards, including data privacy laws. Manage large volumes of data, focusing on accuracy, integrity, and secure accessibility. Develop and refine data processes for data modeling, mining, and production. Implement quality checks, data validation, and monitoring of data flows. Collaborate with data scientists, analysts, and IT teams to meet data requirements. Work closely with data architects and modelers on project objectives and solutions. Troubleshoot and resolve issues in data pipelines, ensuring performance tuning and optimization. Develop and implement disaster recovery procedures to safeguard data. Ensure seamless integration of HR and other business data into cloud-based environments. Research new opportunities for data acquisition and discover additional uses for existing data. Stay up-to-date with the latest cloud technologies, data management practices, and trends, including Generative AI. Recommend and implement improvements to enhance data reliability, efficiency, and quality. Your Profile: 10+ years of experience in cloud data engineering. Proficiency with cloud platforms such as AWS, Azure, or Google Cloud. Experience with data pipeline tools like Apache Spark, AWS Glue, or similar technologies. Strong programming skills in Python, SQL, Java, or Scala. Familiarity with Snowflake, Informatica, or similar tools is an advantage. In-depth knowledge of data privacy laws, security best practices, and data governance. Expertise in analyzing and interpreting complex datasets to derive actionable insights. Strong communication, collaboration, and problem-solving skills. Knowledge of database technologies, including SQL, Big Data, and Cloud-based systems. Passion for learning and keeping up with emerging technologies, particularly in Generative AI. Experience working in an Agile framework and managing multiple projects simultaneously. Ability to adapt to evolving priorities and business needs. What You Will Love About Working Here: Flexibility: Enjoy flexible work arrangements such as remote work or flexible hours, ensuring a healthy work-life balance. Career Growth: We offer numerous opportunities for career advancement and personal development, helping you explore diverse paths and expand your skills. Certifications & Learning: Gain valuable certifications in cutting-edge technologies, including Generative AI, to stay ahead of the curve. About Capgemini: Capgemini is a global business and technology transformation partner that helps organizations accelerate their dual transition to a digital and sustainable world. With a team of 340,000 professionals in over 50 countries, we are dedicated to making a tangible impact on enterprises and society. Trusted by clients for over 55 years, Capgemini uses its deep industry expertise and cutting-edge technologies such as AI, cloud, and data to unlock the full potential of businesses worldwide. In 2023, the group reported global revenues of 22.5 billion.

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!