Technical Screening Round 1 (45–60 mins) Focus Areas: SQL: Joins, CTEs, Window Functions, Optimization Azure Data Factory: Pipelines, Triggers, Linked Services Azure Data Lake, Blob Storage: Structure, Access Data modeling: Star/Snowflake schema ETL/ELT Scenarios 🧪 Example Questions: How do you handle schema drift in ADF? Difference between copy activity and data flow in ADF? Write a query to get 2nd highest salary from a table. 3. Technical Deep Dive / Hands-On Round Focus Areas: Spark / PySpark or Scala (if required) Azure Databricks: notebooks, transformations Delta Lake / Lakehouse architecture Data partitioning, performance tuning Real-time vs batch pipelines 🧪 Example Questions: How do you optimize a large join in Databricks? What's the difference between Delta Lake and Parquet? Show a sample notebook code for transforming a nested JSON