Python questions from TCS data engineering interviews.
These python questions are sourced from TCS data engineering interviews. Each includes an expert-level answer. This set leans toward fundamentals — 3 easy, 0 medium, and 0 hard questions. Recurring themes are spark and python — 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 3 curated questions: 3 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 spark (2), and python (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.
Can you give an example of processing nested JSON data using these functions?
How do you install a Python library that is not in the Databricks runtime?
When would you use flatten, explode, or collect_list in Spark?
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