Medium-level behavioral questions from real data engineering interviews.
These medium behavioral questions are selected from real interviews at top companies. Each question includes a detailed expert answer and pro tip to help you nail your interview. This set leans toward the medium-difficulty band most real interviews actually live in (18 of 18). Recurring themes are partition, join, and spark — these patterns appear most often in real interviews and reward the deepest preparation. These questions have been reported across 19 companies including Delivery Hero and Grover. Average answer is around 1 minute of reading — plan roughly 1 hour to work through the full set thoughtfully.
This collection contains 18 curated questions: 0 easy, 18 medium. The balanced mix of difficulties makes this set suitable for engineers at any career stage.
The most frequently tested areas in this set are partition (10), join (8), spark (5), airflow (2), and lakehouse (1). Focusing on these topics will give you the highest return on your preparation time.
Medium-difficulty questions form the bulk of real interviews — spend the most time here and practice explaining your reasoning out loud. 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.
Tell me about a time when you faced a challenging situation at work and how you handled it.
What challenges did you face, and how did you tackle them?
What would you do if a pipeline failed and you couldn't find the reason?
Why do you want to join this company?
Describe a time when you went above and beyond for a project or a customer.
Give an example of a time you failed and what you learned from it.
Can you provide an example of a time when you went above and beyond for a project?
Examples of conflicts with team members and how they were resolved.
How do you handle conflict with a product manager?
Share a time when you had to explain a complex technical issue to a non-technical stakeholder.
Tell me about a time when a Spark job failed in production. How did you fix it?
Tell me about a time when you faced a tight deadline in a project, and how did you manage it?
Tell me about a time you handled a data pipeline failure during a critical operation.
What challenges can arise when using high degrees of parallelism?
What challenges did you encounter when scaling your project?
What storage format would you choose for analytics-heavy workloads and why?
Why do you want to join American Express?
Why do you want to join EPAM?
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