Manage and monitor ETL/ELT pipelines, analytics reporting jobs, ML workflows across Azure services, ensuring SLA compliance and the timely resolution of Incidents, failures and performance bottlenecks.

Proactively monitor platform health, performance, and SLAs using Databricks monitoring, logging and alerting, to minimize downtime and data issues.

Perform root cause analysis and implement long term fixes that prevent recurring issues and improve overall operational reliability.

Partner with data engineers, ML engineers, and BI engineers to troubleshoot issues, implement improvements, automate operations, and drive continuous enhancement of data/ML platform reliability.

Contribute to platform automation, CI/CD for data/ML pipelines.

Provide support for tools that are owned by Enterprise Data Management.

Develop and maintain code enhancements, automation scripts that support both data engineering and operational needs.

Provide after-hours support for critical systems and applications.

Develop and maintain documentation, runbooks, and operational standards.

Strong experience in SQL, Python and PySpark

Extensive hands-on experience with Azure Databricks with Unity Catalog, ADF, ADLS

Excellent problem-solving skills and attention to detail.

Strong communication and collaboration abilities across technical and non-technical teams.

Roles and Responsibilities

Manage and monitor ETL/ELT pipelines,



analytics reporting jobs, ML workflows across Azure services, ensuring SLA compliance and the timely resolution of Incidents, failures and performance bottlenecks.

Proactively monitor platform health, performance, and SLAs using Databricks monitoring, logging and alerting, to minimize downtime and data issues.

Perform root cause analysis and implement long term fixes that prevent recurring issues and improve overall operational reliability.

Partner with data engineers, ML engineers, and BI engineers to troubleshoot issues, implement improvements, automate operations, and drive continuous enhancement of data/ML platform reliability.

Contribute to platform automation, CI/CD for data/ML pipelines.

Provide support for tools that are owned by Enterprise Data Management.

Develop and maintain code enhancements, automation scripts that support both data engineering and operational needs.

Provide after-hours support for critical systems and applications.

Develop and maintain documentation, runbooks, and operational standards.

Robust experience in SQL, Python and PySpark

Extensive hands-on experience with Azure Databricks with Unity Catalog, ADF, ADLS

Excellent problem-solving skills and attention to detail.

Strong communication and collaboration abilities across technical and non-technical teams.

📌 Lead Data Operations Engineer (Bengaluru)
🏢 Tavant
📍 Bengaluru