Spark & Big Data questions from Expedia data engineering interviews.
These spark & big data questions are sourced from Expedia data engineering interviews. Each includes an expert-level answer. This set leans toward senior-level depth (3 of 3 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 3 curated questions: 0 easy, 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 optimization (3), partition (3), spark (3), join (2), sql (1), and window (1). Focusing on these topics will give you the highest return on your preparation time.
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.
Conceptualize and design a real-time streaming data pipeline end-to-end.
Explain Apache Spark fundamentals, OOM scenarios and their resolutions, optimization techniques, strategies for optimized joins, and handling data skewness with Key Salting techniques.
How can Docker be used to scale streaming data applications?
Get full access to 1,800+ expert answers, AI mock interviews, and personalized progress tracking.