General questions from Dunnhumby data engineering interviews.
These general questions are sourced from Dunnhumby data engineering interviews. Each includes an expert-level answer. This set leans toward senior-level depth (3 of 7 are tagged hard). Recurring themes are snowflake, sql, and bigquery — these patterns appear most often in real interviews and reward the deepest preparation. Many of these questions also surface at Aarete and Fragma Data Systems, so the preparation transfers across companies. Average answer is around 1 minute of reading — plan roughly 1 hour to work through the full set thoughtfully.
This collection contains 7 curated questions: 2 easy, 2 medium, and 3 hard. The distribution skews toward harder problems, reflecting the depth expected in senior-level interviews.
The most frequently tested areas in this set are snowflake (4), sql (4), bigquery (3), etl (3), partition (3), and join (3). Focusing on these topics will give you the highest return on your preparation time.
Start with the easy questions to warm up and solidify fundamentals. Medium-difficulty questions form the bulk of real interviews — spend the most time here and practice explaining your reasoning out loud. Hard questions often appear in senior and staff-level rounds; attempt them after you're comfortable with the basics. For each question, try answering before revealing the solution. Use our AI Mock Interview to simulate real interview conditions and get instant feedback on your responses.
Have you worked on Data Warehousing projects?
What is the difference between OLTP and OLAP?
What is the difference between SQL and NoSQL databases?
Explain your projects on which you worked till now and what was your role?
Name the tools and technologies you have worked with to date.
What steps do you take to troubleshoot a slow-running Spark job?
What would you do if you were assigned a task with a technology you've never used before?
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