- Pipeline Orchestration: Use Fabric Data Factory to orchestrate Azure Databricks jobs ( Python scripts).
- Lakehouse Implementation: Design and maintain using Delta Lake.
- Data Integration: Land data from Databricks directly into Fabric OneLake or create shortcuts to access Databricks Delta files without moving data.
- ETL/ELT Development: Develop high-performance processing applications using PySpark, Spark SQL, and Python.

Key Technical Skills

- Cloud Platforms: Deep expertise in the Azure Data Stack, specifically Azure Data Lake Storage (ADLS) and Azure Synapse.
- Languages: Proficiency in Python, SQL, and occasionally Scala or Java for custom Spark development.
- Fabric Tools: Hands-on experience with Fabric Lakehouse, Data Warehouse, and Power BI integration (Direct Lake mode).
- DevOps: Familiarity with CI/CD pipelines (Azure DevOps/GitHub Actions) for automating data workload deployments. [1, 2, 3, 4, 5, 6, 7]

Qualifications & Experience

- Experience: Typically 5++ years for mid-level and 5-8+ years for SenioR Data Engineer roles.

📌 MS Fabric - Pan India -2nd Sep (Wednesday)- 5-14 years-Video Interview
🏢 Tata Consultancy Services
📍 India