Round 1: Technical Screening (30 mins)

Project Discussion: Talked about recent project using Azure and Spark.

SQL Questions (2): Focused on window functions

PySpark Questions (2): Questions on window functions and case when statements

Round 2: Client

Experience Discussion: Deep dive into previous work, tools used (Spark, ADF, Azure Data Lake).

SQL - Two question on join conditions, 1 question on window functions

Spark Optimization:

- Broadcast joins

- Repartition vs Coalesce

- Data skew handling

Round 3: Databricks + Scenario-Based

Unity Catalog:

- What it is and how it helps with data governance.

- Access control at table, schema, and row level.

Delta Lake:

- Schema evolution

- MERGE operations

Round 4: HR

- Resume overview

- Role expectations

- Joining date and preferred location