Top Data Engineer Jobs in Chennai

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.

The Senior Data Engineer will design and optimize ETL/ELT pipelines, manage data integration, perform data validation, and support reporting solutions using various technologies.

This role involves leading SAP data migration projects, developing ETL processes, ensuring data quality, and collaborating with cross-functional teams to optimize data integration and management strategies in SAP environments.

Lead Data Engineer to design, build, and operate production data pipelines, retrieval/vector infrastructure, semantic/feature stores, and ML/LLMOps foundations. Drive CI/CD, governance, monitoring, and agent/data APIs for RAG, LLM, and predictive model workloads.

Lead the architecture and implementation of a distributed data platform for microscopy, ensuring scalability and high-performance in data management.

Design, build, monitor and scale an enterprise data warehouse and pipelines. Lead data integration, ETL design, source-to-target mapping, reusable frameworks, automated testing/CI, and partner with stakeholders to deliver secure, governed analytics for product, marketing and HR use cases.

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.

As a Lead Data Engineer, you will design and manage data pipelines, develop ETL processes, and ensure data quality. Mentorship of junior engineers is also part of the role.

Develop and scale data management systems for AutoML and forecasting platforms, ensuring data reliability and implementing SLAs across pipelines.

As a Lead Engineer, you'll design and develop frameworks and services for HighLevel's platform, optimizing large-scale database clusters and ensuring performance and security across multiple environments.

Design and develop large-scale database systems, optimize performance, and implement automation for managed database services. Collaborate across teams to enhance data access and ensure governance for security and compliance.

As a Senior Data Engineer, you will architect the AI-native Data Platform, optimize performance, ensure data governance, and mentor engineers on best practices.

Lead site-based CSA activities for data centre projects: manage contractors, ensure compliance with design, safety and quality, coordinate stakeholders, produce reports, and support project leadership.

Lead Azure Data Engineer to design, build, and operate petabyte-scale data systems on Azure. Lead a data engineering team to develop ETL pipelines (ADF, Synapse, Databricks), perform data modelling, migrations, monitoring, security, and collaborate with BI/ML/Product teams while mentoring junior engineers and improving analytics and dashboarding.

The Senior Data Scientist & Engineer will build and manage data infrastructure, analyze product usage, build models, track metrics, run experiments, and communicate insights to guide product decisions.

Design, build, and optimize ELT data pipelines using Python, Airflow DAGs, and Spark in cloud environments. Convert and debug Microsoft BI ETLs into scalable big-data workflows, tune Spark resources, collaborate with business partners, and participate in Agile ceremonies with Pacific-time overlap.

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.

Design, build, optimize, and deploy large-scale Spark/Scala data processing and ETL pipelines on Cloudera (CDH). Collaborate with data teams, ensure data integrity and security, troubleshoot performance, and implement version control and CI/CD for Spark applications.

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, develop, test, and deploy high-performance Spark/Scala data processing applications and ETL pipelines on Cloudera (CDH). Optimize Spark and Cloudera platform performance, integrate HDFS/Hive/Impala/HBase/Kafka, ensure data integrity/security, and implement version control and CI/CD for production pipelines.

Lead end-to-end customer data integration and migration projects using SQL, ETL, and scripting. Act as technical advisor, design tailored solutions, manage 10–15 projects, document requirements, mentor juniors, and collaborate with government stakeholders and cross-functional teams to improve and automate data workflows.

Triage and resolve Master Data Management (Party, Risk, Reference) issues in Stibo STEP, run targeted data-cleansing sprints, monitor data quality dashboards, support releases/UAT, and maintain documentation and playbooks to prevent recurring data issues.

The Big Data Engineer will support existing applications and work on new design and implementation requirements, utilizing big data technologies and tools.

The role involves data analytics with a focus on querying large data sets, visualization using Tableau, and applying quantitative skills, predominantly in the FMCG and Food & Distribution sectors.

The Data Analyst prepares, analyzes, and validates data, applying statistical methods and visualization techniques to derive insights and support business objectives. Communicates findings effectively and collaborates with Data Engineers for model and dashboard implementation.