Python questions from Gartner data engineering interviews.
These python questions are sourced from Gartner data engineering interviews. Each includes an expert-level answer. This set leans toward fundamentals — 5 easy, 0 medium, and 0 hard questions. Recurring themes are python and spark — these patterns appear most often in real interviews and reward the deepest preparation. Average answer is around 1 minute of reading — plan roughly 1 hour to work through the full set thoughtfully.
This collection contains 5 curated questions: 5 easy. There's a strong foundation of fundamentals-focused questions — ideal for building confidence before tackling advanced topics.
The most frequently tested areas in this set are python (2), and spark (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. 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.
Compare compression algorithms: Gzip vs Snappy.
Create a dictionary with list elements as keys and their occurrences as values.
Explain Lambda functions in Python.
Explain this code: [f(2) for f in [lambda x: x * i for i in range(5)]].
Write a swap function without if-else.
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