Top DevOps Jobs in Chennai

Leads a platform engineering team responsible for cloud infrastructure, Kubernetes, automation, Infrastructure as Code, CI/CD, and developer enablement. Sets technical priorities and roadmaps, drives platform reliability, incident response, observability, security, and operational excellence, and partners across engineering, product, architecture, infrastructure, and security teams. Coaches engineers, manages resources and delivery, establishes engineering standards and metrics, and advances DevOps, GitOps, and cloud-native practices.

Lead and architect front-end UI systems, translate complex requirements into working software, drive troubleshooting and root-cause analysis, engage senior architects on automation roadmap, write and debug code, configure CI/CD pipelines, and lead a team of software engineers to deliver features.

End-to-end UI full-stack development for a SaaS security, risk, and compliance platform. Build frontend components (React) and backend services/APIs (Python/Django REST), design cloud-hosted microservices, ensure resilience, implement security features (DevSecOps), support production deployments and incident triage, create reusable web components, collaborate with product/UX/DevOps in an Agile environment.

Design, develop, and maintain scalable CI/CD pipelines, automation solutions, and infrastructure automation for cloud-native platforms. Support DevOps processes, troubleshoot production/platform issues, build reusable tools and frameworks, collaborate with cross-functional teams, and drive modernization, security, reliability, and operational efficiency.

Lead and manage software engineering teams while ensuring code quality and timely delivery of enterprise-grade applications, providing technical oversight and mentorship.

Design, build, and maintain Java-based cloud-native backend services and microservices for a fraud platform. Contribute to system design, CI/CD, integrations, performance, and production reliability. Mentor junior engineers and collaborate across product, architecture, DevOps, and cross-functional teams in a hybrid environment.

The Principal Software Engineer will manage API Gateway platforms, ensuring scalability, security, and automation, while leveraging AI for operational efficiency and incident response.

Design, build, and scale high-performance backend systems in Golang. Lead system and API design, cloud-native microservices, observability, secure coding, and AI/ML integrations. Mentor junior engineers and collaborate with DevOps, QA, and platform teams to deliver reliable, testable solutions.

Designs, implements, automates, and supports secure AWS cloud infrastructure and Kubernetes platforms. Builds CI/CD pipelines and Infrastructure as Code, integrates DevSecOps controls, manages monitoring and observability, automates processes, and supports production incidents. Collaborates with engineering, QA, MLOps, and security teams across cloud and hybrid environments while driving reliability, vulnerability remediation, governance, and operational excellence independently.

Build, maintain, and optimize scalable batch and real-time data pipelines using PySpark, Spark, Python, SQL, and ETL/ELT tools. Design cloud-based data platforms, data lakes, ingestion strategies, and Big Data processing frameworks across AWS, Azure, or GCP. Ensure data quality, security, governance, performance, and availability while collaborating with architects, analysts, data scientists, and engineers.

Designs, develops, tests, operates, and maintains reliable full-stack software products. Responsibilities include writing production-ready code, creating scalable architectural designs, analyzing failures, conducting code reviews, applying security and compliance practices, and improving software reliability. The engineer collaborates across product teams, participates in agile and DevOps processes, communicates blockers, and contributes to continuous improvement and technology transformation.

Build, maintain, and optimize scalable data pipelines and ETL/ELT processes using PySpark, Spark, and Python. Design cloud-based data engineering solutions across AWS, Azure, or GCP; support data lakes, batch and streaming workloads, and data ingestion strategies. Collaborate with data scientists and analysts, improve Spark performance, maintain reusable code, and support data governance, security, and CI/CD practices.

Designs, builds, maintains, and optimizes scalable data pipelines and ETL/ELT processes using Databricks, PySpark, and Spark. Supports cloud data architecture across AWS, Azure, or GCP; develops batch and real-time processing solutions; manages data lakes and ingestion strategies; and collaborates with data scientists, analysts, and engineers. The role also contributes to performance tuning, governance, data security, troubleshooting, and reusable data engineering code.

Build, maintain, and optimize scalable batch and real-time data pipelines using Databricks, PySpark, Spark, Python, and cloud platforms. Develop ETL/ELT processes, data ingestion strategies, data lakes, and big data frameworks. Collaborate with analysts, data scientists, and engineers to ensure data quality and availability. Tune pipeline performance, support governance and security, and contribute to cloud deployments, orchestration, streaming, and DevOps practices.

Builds, maintains, and optimizes scalable batch and real-time data pipelines using Databricks, PySpark, Spark, Python, and cloud platforms. Develops ETL/ELT processes, data lakes, ingestion strategies, and Big Data frameworks. Collaborates with architects, data scientists, analysts, and engineers to ensure data accuracy and availability. Supports performance tuning, governance, security, orchestration, and deployment of cloud-native data solutions.

Leads enterprise-scale Databricks lakehouse architecture and implementation, designing governed data platforms, scalable ETL/ELT pipelines, data models, integrations, security policies, and real-time analytics. Collaborates across data science, analytics, and platform teams while providing client leadership, execution ownership, performance optimization, and technical guidance on Unity Catalog, Delta technologies, data sharing, BI integrations, and advanced AI capabilities.

Builds, maintains, and optimizes scalable batch and real-time data pipelines using Databricks, Spark, PySpark, and cloud platforms. Develops ETL/ELT and ingestion processes, supports data lakes and Big Data frameworks, tunes performance, and maintains governance and security practices. Collaborates with architects, data scientists, analysts, and engineers to ensure reliable data integration, accuracy, and availability.

Build, maintain, and optimize scalable batch and real-time data pipelines using PySpark, Spark, Python, and cloud platforms. Develop ETL/ELT processes, data ingestion strategies, data lakes, and Big Data frameworks. Collaborate with data scientists, analysts, and engineers to ensure data quality and availability. Tune performance, maintain reusable code, and support governance, security, CI/CD, and cloud-native data solutions.

Build, maintain, and optimize scalable data pipelines and ETL/ELT processes using PySpark, Spark, Python, and cloud platforms. Support data lakes, big data frameworks, real-time streaming, batch processing, data ingestion, governance, and security. Collaborate with data scientists, analysts, and engineers to ensure data availability and accuracy. Tune pipeline performance, troubleshoot issues, and contribute to cloud-native data architecture and DevOps practices.

Build, maintain, and optimize scalable batch and real-time data pipelines using Python, PySpark, Spark, and cloud platforms. Develop ETL/ELT processes, data ingestion strategies, data lakes, and Big Data frameworks. Collaborate with architects, analysts, data scientists, and engineers to ensure data accuracy and availability. Support streaming workloads, Spark performance tuning, governance, security, orchestration, and CI/CD practices across cloud environments.

Leads the architecture and implementation of enterprise Databricks lakehouse platforms. Designs scalable data ingestion, transformation, governance, security, anonymization, sharing, and analytics solutions using technologies such as Delta Lake, Unity Catalog, DLT, and PySpark. Provides hands-on technical leadership, performance optimization, cloud guidance, client engagement, cross-functional coordination, and people development. Integrates governed data platforms with BI tools and advances capabilities including Mosaic AI, Vector Search, and Model Serving.

Leads enterprise-scale Databricks lakehouse architecture and implementation, including data ingestion, transformation, governance, security, sharing, performance optimization, and BI integration. Designs scalable pipelines using Python, PySpark, Delta Lake, Auto Loader, and Delta Live Tables. Establishes Unity Catalog governance, privacy controls, and cross-platform access. Provides client leadership, technical guidance, people development, and thought leadership on advanced Databricks, AI, and data product capabilities.

Designs, builds, maintains, and optimizes scalable data pipelines and ETL/ELT processes using Databricks, PySpark, Spark, and cloud platforms. Supports data lakes, batch and real-time processing, ingestion strategies, governance, security, and performance tuning. Collaborates with data scientists, analysts, and engineers to ensure reliable data availability and accuracy while contributing to cloud deployments, reusable code, and modern data engineering practices.

Build, maintain, test, and optimize scalable data architectures and pipelines. Extract, transform, and load data for analysts and scientists; source and integrate new data; improve data quality, security, governance, reliability, and performance. Collaborate with technology and architecture teams, practice DevOps, troubleshoot issues, manage platform costs, and contribute to strategic data solutions.

Designs, develops, tests, operates, and maintains production software products. Owns full-stack delivery, writes reliable and testable code, applies architectural best practices, analyzes failures, conducts code reviews, and ensures compliance and security. Collaborates across product teams, communicates blockers, supports continuous improvement, and mentors junior engineers while contributing to agile and DevOps practices.