It was smooth, Got a call for first round, started with intro and project I've worked on, as it was technical focused more on pyspark and sql. Data Engineering principles and processes.

The interview was all based upon python, spark and sql. Questions were easy to moderate level. Mostly from python and sql. Questions like : a table consists of some positive and some negative integers. Write a query to create a new table and to separate positive integers in positive _numbers column and negative integers in negative_numbers column

First Round was in-depth on Spark. Advanced Spark Internals, Driver-executor Memory Management in Spark Task Scheduling and Execution, and review DAG in depth Execution plans, physical and logical plan, Catalyst Optimizer, AQE in depth with example Structured Streaming Dynamic Resource Allocation in Spark Handling Skewed Data Job Failures and Retry Mechanisms Types of schedulers Default join types and differences Change Broad cast join defaults