Round 1: Online Assessment (55 minutes)

✅ ETL (Extract, Transform, Load) - Concepts and scenarios in ETL pipelines.

✅ Data Warehousing - Star schema, snowflake schema, and their applications.

✅ SQL - Writing complex queries.

✅ Data Modelling - Creating efficient data models.

✅ AWS (Amazon Web Services) - Services like S3, Redshift, or Lambda.

✅ Python - Coding and scripting for data processing.

✅ Analytical Ability / Puzzles / Guesstimates - Logical reasoning and problem-solving.

Round 2: Technical Interview (60 minutes)

✅ SQL Questions

🔹 Writing queries involving joining 3 tables.

🔹 Rank vs Dense Rank: Differences and use cases.

🔹 Union vs Union All: Performance and behavior.

🔹 Indexing

🔹 Advantages and disadvantages of database indexing.

✅ Basic Spark Architecture

🔹 Understanding Spark components like Driver, Executor, and Cluster Manager.

🔹 Performance Tuning in Spark

🔹 Techniques to optimize Spark jobs.

✅ Data Skewness in Spark

✅ Real-Time Data Engineering Pipeline

✅ Asynchronous vs Synchronous Processing

✅ Company Project

✅ Deep Dive into the Tech Stack of Past Projects

✅ Facts and Dimensions

✅ Design a Simple Data Model

✅ Create a basic data model and define facts and dimensions.

Round 3: Technical + Managerial Interview (30 minutes)

✅ Why ZS?

✅ Why Consulting?

✅ Is Communication Important for a Data Engineer in a Consulting Firm?

✅ Where Do You See Yourself in the Next 5 Years?

✅ Past Experience and High-Level Project Overview

✅ Challenges Faced with Managed Airflow

Round 4: HR

✅ Offer Discussion Round (15 minutes)

✅ The salary structure was explained.