Interview questions
Preparing for a data engineering interview at Microsoft? This page contains 21 real interview questions sourced from verified Microsoft interview experiences. Questions are sorted by frequency — the ones asked most often appear first.
Microsoft data engineering interviews typically focus on Spark/Big Data, System Design/Architecture, and SQL. The interview bar skews toward harder problems (9 hard vs. 6 easy), suggesting emphasis on depth and system-level thinking.
Use the difficulty filters above to focus your preparation. For each question, attempt your own answer first, then compare with our expert solution. You can also practice these questions in our AI Mock Interview Coach for real-time feedback.
When would you choose a Snowflake schema over a Star schema?
How do you ensure data quality and validation in a fast-moving team?
Tell me about a time when a Spark job failed in production. How did you fix it?
What storage format would you choose for analytics-heavy workloads and why?
What happens if the NameNode goes down?
What's the time and space complexity of both solutions?
Given a list of intervals, merge the overlaps. How do you optimize it?
How would you test these functions with edge cases?
Solve the Dutch National Flag problem in one pass. How would you handle it?
How do partitions improve query performance in fact tables?
What's the role of surrogate keys in dimensional modeling?
Compare Spark and MapReduce for iterative workloads
Explain how Spark groups transformations into stages. What causes a stage boundary?
How do you set up CI/CD for a PySpark ETL workflow?
How is resource allocation handled in YARN?
What's the difference between narrow and wide transformations?
When would you choose a broadcast join over a shuffle join? Any memory risks?
Design a data model to track orders, payments, and shipping — handle changes in customer address
Design a data pipeline to ingest and process clickstream data in near real-time
How does HDFS handle fault tolerance?
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