Interview Prep Hub
Crack Your Next
Data Engineering Interview
Handpicked Spark, SQL, Python, Kafka & Hive questions — with real explanations, code examples, and the depth interviewers actually test.
11 Interview Tracks
Choose Your Topic
Each track covers conceptual depth, coding patterns, and system design questions aligned with real interviews.
PySpark & Apache Spark Interview Questions
RDDs vs DataFrames, DAG execution, transformations vs actions, lazy evaluation, shuffle, partitioning, and memory management — the depth FAANG interviewers test.
PySpark Coding Interview Questions
Hands-on PySpark problems: joins, window functions, aggregations, UDFs, broadcast variables, and performance tuning scenarios you will write live in interviews.
SQL Interview Questions for Data Engineers
Window functions, CTEs, subqueries, GROUP BY pitfalls, indexing strategy, and query optimization — covering everything from junior to senior SQL rounds.
Data Engineering System Design
Design a real-time pipeline, data lakehouse, CDC system, or batch ETL at scale — covering Lambda vs Kappa, partitioning strategies, idempotency, and fault tolerance.
Senior Data Engineer Interview Questions
Architecture trade-offs, data contracts, platform design, SLA ownership, cross-team collaboration, and leadership scenarios — questions for 5+ years experience roles.
Databricks Interview Questions
Delta Lake, Unity Catalog, Databricks Workflows, Auto Loader, Photon engine, cluster configuration, and Lakehouse architecture — real questions from Databricks-stack interviews.
Azure Data Engineer Interview Questions
Azure Data Factory, Synapse Analytics, ADLS Gen2, Event Hubs, Azure Databricks, and cloud data architecture patterns — for DP-203 certified and hands-on Azure DE roles.
Apache Airflow Interview Questions
DAGs, operators, XComs, sensors, task dependencies, scheduling strategies, and Airflow architecture — questions asked for data pipeline and orchestration roles.
Python Interview Questions for Data Engineers
Data structures, OOP, decorators, generators, list comprehensions, pandas, and scripting patterns for data engineering pipelines and ETL workflows.
Apache Kafka Interview Questions
Topics, partitions, consumer groups, offset management, exactly-once semantics, Kafka Streams vs ksqlDB — real streaming architecture questions asked at scale-up companies.
Apache Hive Interview Questions
HiveQL, partitioning vs bucketing, ORC vs Parquet, SerDe, metastore architecture, and Tez vs MapReduce — for data warehouse and Hadoop ecosystem interviews.
Why PySpark.in
Built for real interviews, not memorisation
Targeted by Role
Questions curated for Data Engineer, Analytics Engineer, and ML Engineer roles at top companies.
Deep Explanations
Every answer explains the "why" — not just what the correct answer is, but why interviewers ask it.
Code + Concepts
Runnable PySpark and SQL examples you can try in the browser — no setup required.
Always Updated
Community-contributed questions keep the bank fresh with patterns from recent interviews.