Top Data Engineer Jobs in Chennai

Join the Event Streaming and Data Replication platform as a Data Engineer to design, build, and operate cloud-native data platforms. Work with Airflow, Spark, Kubernetes, and Python; deploy containerized apps on AWS/Azure; use IaC (Terraform/CFT/ARM); implement CI/CD (GitHub, Artifactory, Jenkins); configure monitoring and alerts; and collaborate across teams to deliver highly available, scalable solutions.

Design, build, and maintain ELT/data pipelines and workflow orchestration using Airflow, Python, and PySpark. Develop custom connectors to ingest diverse data, implement DataOps and data CI/CD pipelines, monitor and troubleshoot pipelines, validate data quality, collaborate with cross-functional teams, document workflows, and work with large-scale distributed datasets and visualization tools.

Design, build, and optimize ETL pipelines and data warehouses using SQL, AWS Glue, and S3. Investigate and resolve data issues, develop Python-based solutions and small web apps, and own requirements, design, and end-to-end delivery for change requests.

Provide onsite acquisition and analysis of drilling data during rig operations, install and maintain GEOLOG systems, perform real-time monitoring, generate technical logs and reports, act as first-line client technical support, and manage/train mud logging team while ensuring rig safety compliance.

Lead the data team to build scalable data products, create data pipelines, partner with business teams, and ensure data quality while impacting revenue and decision-making.

Owner of company-wide reporting and analytics for Growth, Marketing, Product, Finance and Operations. Build and maintain dashboards, automated reports and data pipelines (dbt), ensure data quality and governance, run growth and product analyses (CAC, ROAS, LTV, retention), support A/B testing and ad-hoc decision support, leverage AI for automation, and coordinate VAs on data tasks.

Lead data science initiatives for Quvia’s connectivity platform by developing predictive, prescriptive, forecasting, classification, and optimization models. Integrate anomaly detection, knowledge graphs, neural networks, and generative AI into products; deploy and continuously refine production-ready models; establish data quality and governance standards; document workflows; and mentor junior data scientists while collaborating cross-functionally with engineering and product teams.

Design, develop and maintain data pipelines, optimize data architectures, and collaborate with data scientists while ensuring data quality and governance.

Design, implement, and maintain data pipelines using Elasticsearch and data warehousing solutions, integrate data sources, and ensure data accuracy while collaborating with cross-functional teams.

As a Data Engineer, you will build scalable ETL/ELT pipelines, optimize data structures, and develop impactful Power BI solutions for stakeholders.

The Data Engineer will design and maintain data models, develop BI solutions, integrate data, and optimize data flows while collaborating with stakeholders.

The Senior Data Platform Engineer will architect and optimize Hexnode's data infrastructure for high-volume security telemetry and analytics, ensuring scalability, efficiency, and data security.

Design, develop, and support enterprise data platforms, ETL/ELT pipelines, Oracle databases, data warehouses, and risk and regulatory reporting solutions. Build automation, optimize SQL and data processing, ensure data quality, reconciliation, lineage, governance, and audit readiness. Provide L2/L3 production support, resolve incidents, manage batch operations, and perform root-cause analysis. Collaborate with Risk, Finance, Regulatory, Business, and Technology stakeholders while mentoring junior team members.

The Senior Data Engineer will architect and implement cloud data platforms, leading a team to deliver high-performance solutions and collaborate with product teams on data transformation initiatives.

The role involves building and scaling the Acceldata Open Data Platform, focusing on observability, coding, debugging, and collaborating with teams and the open-source community.

Build and enhance enterprise data pipelines into Databricks Unity Catalog and Delta Lake. Improve remediation and entity-matching layers (including D&B DataBlocks), integrate APIs, and support LLM-assisted remediation and CMG redesign projects.

Design, build, and maintain scalable Microsoft Fabric and Azure-based data platforms, ETL/ELT pipelines, lakehouse and data warehouse architectures. Implement orchestration, monitoring, data quality, CI/CD, and support analytics, AI, and production operations while following Specification-Driven Development practices.

Lead and contribute to design, architecture, and hands-on development of scalable data platforms and ETL pipelines on cloud (GCP). Drive best practices, CI/CD, integrations, API specs, code reviews, and collaborate with product and stakeholders to deliver high-availability, big-data solutions and BI reporting.

Design and implement distributed data systems for Apache Hudi and Onehouse’s managed data lakehouse. Responsibilities include developing concurrency controls, transactional capabilities, indexing schemes, metadata and data-access systems, and optimization algorithms for Kubernetes-based distributed processing. The role involves analyzing complex data, prototyping performance improvements, deploying solutions safely to production, and serving as a subject matter expert in databases, query engines, storage, and stream processing.

Build and productionize distributed data infrastructure for Onehouse’s managed lakehouse platform. Responsibilities include developing Apache Hudi transactional capabilities, concurrency control, indexing, metadata and data-access systems, and optimization algorithms for distributed processing on Kubernetes. The role involves analyzing complex data, prototyping performance improvements, collaborating with engineers, and safely deploying solutions. Candidates should bring strong object-oriented programming, distributed systems, algorithm, and relational database expertise.

Design, deploy, and maintain AWS and Databricks data infrastructure, data lakes, and scalable ETL pipelines. Build custom ingestion services and connectors using Airbyte, Go, and Python; optimize performance, reliability, monitoring, and data quality. Implement cloud data governance, security, access controls, encryption, and compliance practices while collaborating with platform engineers, analysts, and stakeholders.

The Data Engineer role involves designing and maintaining ETL pipelines, optimizing data storage solutions, collaborating with teams, and ensuring data accuracy and integrity.

Lead test engineering teams to design and execute system integration and automated tests across UI, services, and APIs. Develop and maintain reusable automation frameworks, test plans, and procedures; partner with product, development, and DevOps; track execution, risks, and environment/data dependencies; ensure process compliance and mentor junior engineers.

Design, implement, and optimize Apache DolphinScheduler workflows and ETL pipelines. Integrate with Hadoop, Spark, Flink, Hive, and Kafka. Develop custom plugins, troubleshoot performance and scalability issues, monitor job execution and resource allocation, and maintain CI/CD, version control, and infrastructure automation while collaborating with data engineers and DevOps teams.

Design and implement data quality processes, profile and cleanse data, deploy cloud-based data quality solutions (Azure/AWS/GCP), document issues and remediation, report metrics, and collaborate with data teams and stakeholders.