System Design questions from PWC data engineering interviews.
These system design questions are sourced from PWC data engineering interviews. Each includes an expert-level answer. This set leans toward senior-level depth (2 of 4 are tagged hard). Recurring themes are optimization, partition, and spark — these patterns appear most often in real interviews and reward the deepest preparation. Average answer is around 2 minutes of reading — plan roughly 1 hour to work through the full set thoughtfully.
This collection contains 4 curated questions: 1 easy, 1 medium, and 2 hard. The distribution skews toward harder problems, reflecting the depth expected in senior-level interviews.
The most frequently tested areas in this set are optimization (2), partition (2), spark (2), bigquery (1), and join (1). 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.
What are the best practices for logging and monitoring bad data?
What are the implications of enabling schema auto-detection?
Can Schema Evolution lead to data inconsistencies? If so, how do you manage them?
Differentiate between Schema Enforcement and Schema Evolution.
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