- Monitor, maintain, and support enterprise data platforms and production environments.

- Build, manage, and troubleshoot data pipelines using Databricks and Spark.

- Handle production incidents, perform root cause analysis (RCA), and ensure timely issue resolution.

- Develop and maintain data workflows using Airflow.

- Work with Azure services and Unity Catalog to manage enterprise data solutions.

- Collaborate with cross-functional teams to ensure data quality, platform reliability, and operational excellence.

- Participate in on-call support and production maintenance activities.

- Prepare technical documentation and support continuous platform improvements.

Required Skills :

- 5 - 8 years of experience in Data Engineering and DataOps.

- Minimum 3 years of hands-on experience in Data Production Support and Incident Management.

- Strong expertise in :

1. Python

2. Databricks

3. Unity Catalog

4. ADLS (Azure Data Lake Storage)

5. Apache Spark

6. Apache Airflow

7. Data Pipeline Architecture & Design

8. Azure Services (Kubernetes, AVD, Log Analytics Workspace, Azure SQL, Cost Management)

9. Troubleshooting & Root Cause Analysis (RCA)

10. Incident Management

11. Stakeholder Management

- Excellent communication and analytical skills.

Good to Have :

- Terraform

- Kubernetes

- Power BI

- GitLab

- Shell Scripting

- Jira & Confluence

- Feature Leadership experience