Join NTT DATA as a DataOps Engineer in Bangalore, Karnataka, India, to provide essential L2 production support for enterprise data pipelines, ETL/ELT workloads, and Data Ops environments operating on GCP.

This role is crucial for maintaining the health and efficiency of our data infrastructure, requiring proactive monitoring and swift resolution of production issues. You'll be instrumental in ensuring seamless data processing and application performance.

We seek individuals passionate about innovation and growth within an inclusive and adaptable organization. If you're ready to make a significant impact in the digital future, apply now.

As a DataOps Engineer, you will be responsible for L2 production support across enterprise data pipelines and Data Ops environments on GCP. This includes monitoring production pipelines to detect failures, delays, and data or infrastructure issues.

You will troubleshoot and resolve Apache Airflow DAG failures, along with issues on Google Kubernetes Engine (GKE) and Cloud Run services. Your role also involves diagnosing data and application problems within Cloud SQL and BigQuery, and analyzing Python-based data pipelines.

Key duties include performing SQL-based data analysis, handling production incidents per SLAs, conducting root-cause analysis, and coordinating with L3 teams. You will also maintain operational documentation, monitor logs and alerts, and support problem management for continuous improvement.

This position requires a minimum of 4 years of experience in production data platform support, Data Ops, ETL/ELT, or enterprise data-processing environments.

Essential skills include strong hands-on experience with Google Cloud Platform (GCP), Google Kubernetes Engine (GKE), and Kubernetes troubleshooting. Proficiency in supporting Apache Airflow and resolving DAG/task failures is mandatory.

Experience with Cloud Run services, Cloud SQL, and BigQuery is expected, alongside strong working knowledge of Python for debugging data pipelines and robust SQL skills for data validation. Familiarity with analyzing logs, alerts, and monitoring metrics is also required.