Top Data Engineer Jobs in Chennai

Lead a small data engineering team to onboard, migrate, operate, and optimize pipelines on a Databricks-on-AWS lakehouse. Support ingestion, transformation, governance (Unity Catalog, Glue), Delta/Iceberg table patterns, pipeline monitoring, CI/CD, and cross-team collaboration to ensure secure, reliable, and performant enterprise data workflows.

Design, implement, and lead large-scale generative AI and ML systems (LLM fine-tuning, RAG, agents, Graph ML). Build REST APIs, deploy with Docker/Kubernetes, optimize big-data workflows, mentor engineers, and operate ML services on cloud platforms.

Own and automate end-to-end incentive calculation pipelines, translate business rules into auditable data workflows, build monitoring and reconciliation dashboards, ensure accuracy and auditability across multiple products and countries, and partner with Sales, Finance, and field teams to resolve discrepancies and support escalations.

Build and maintain end-to-end data pipelines using PySpark and SQL on Databricks/Delta. Establish data modeling and pipeline best practices, create AI-ready analytical datasets, troubleshoot pipeline issues, and collaborate with stakeholders to embed business logic and optimize reliability, efficiency, and performance.

Design, build, and operate batch and real-time data ingestion and transformation pipelines. Develop platform components (storage, compute, pipelines), monitoring, alerting, and data-quality tooling. Diagnose production issues, participate in on-call rotations, and build AI-powered agents to automate engineering and operational tasks.

Design, optimize, and manage scalable cloud databases (AWS RDS, BigQuery). Write efficient SQL, build Python data tools using OOP, support pipelines, monitor performance, ensure data integrity, security, and backups, and collaborate with data teams.

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

Design and optimize scalable data platforms using Microsoft Fabric and Databricks; create data pipelines and models for enterprise analytics while collaborating with data science teams.

Design and implement data federation and lakehouse architectures (Starburst/Trino), build scalable ETL/ELT pipelines using Python and Spark, optimize Spark and federated queries, manage Delta/Iceberg/Hudi tables, and enforce governance, access control, and data masking for analytics and AI use.

As a Data Engineer, you'll build and monitor large-scale data pipelines, develop the DBT setup for data transformation and solve customer problems using your SQL skills.

The IT Operations Engineer will manage AI and Data platforms, ensure operational health, lead incident resolution, and automate tasks while collaborating with engineering teams.

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.

Manage and support AKS-based enterprise data platform infrastructure, administer Apache NiFi, Azure Event Hub and Functions, implement CI/CD with Azure DevOps, automate infrastructure with Terraform/Bicep/ARM, monitor with Azure Monitor and Log Analytics, troubleshoot production incidents, ensure security, capacity planning, and collaborate with data engineering teams.

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.

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

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.

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

Design, build, and optimize high-volume data pipelines using Python, Databricks and Spark on Azure. Create and maintain automation test suites (Azure DevOps), perform manual/load/exploratory testing, collaborate with BAs and developers to meet sprint goals, and assist with sprint estimation and delivery.

Design, develop, and deploy data engineering solutions and analytics pipelines on Databricks. Build data models, optimize SQL and DAX queries, manage ETL and real-time ingestion, tune performance for large data volumes, and produce dashboards and reports while cross-training team members.

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.

Senior technical leader responsible for designing, building, and scaling cloud-native data platforms and pipelines. Partners with stakeholders, mentors engineers, enforces engineering best practices, ensures data modeling, governance, and quality, debugs production issues, and contributes to architecture, design, and Agile delivery to support business outcomes.

Design, build, and maintain scalable Java Spring Boot backend microservices integrated with blockchain/Web3 infrastructure. Develop REST APIs, event-driven systems (Kafka/JMS), SQL/NoSQL data stores, and containerized cloud deployments (Kubernetes). Ensure performance, security, and reliability while collaborating with cross-functional teams in Agile environments.

Design, build, and maintain scalable cloud-native batch and streaming data platforms and pipelines. Own end-to-end solutioning, deployment, production support, performance tuning, monitoring, and mentorship while collaborating with product, analytics, and infrastructure teams.

Design, build, and operate scalable batch and real-time data pipelines and analytics platforms. Partner with enterprise customers to define requirements, own technical delivery from discovery to adoption, and present architectures to stakeholders. Drive data governance, observability, CI/CD, and platform optimization while mentoring junior engineers and collaborating with Product, Engineering, and Customer Success teams to enable analytics and AI/ML applications.

Design, build, and optimize large-scale ETL pipelines and distributed data applications (batch and streaming) using Spark and Scala. Ensure data quality and performance, deploy and manage workloads in cloud/container environments, troubleshoot production issues, and collaborate with product, engineering, and analytics teams to deliver scalable AdTech data solutions.