Python questions from Walmart data engineering interviews.
These python questions are sourced from Walmart data engineering interviews. Each includes an expert-level answer. This set leans toward fundamentals — 4 easy, 1 medium, and 2 hard questions. Recurring themes are partition, spark, and optimization — 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 7 curated questions: 4 easy, 1 medium, and 2 hard. 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 partition (2), spark (2), and optimization (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.
Coin Change Problem - minimum number of coins required to make change
Explain and implement Semaphore in Java
Multithreading and Synchronization in Java - write code to manage synchronized threads
Partitioning a Linked List based on a value
The transient Keyword in Java
Write a simple service and controller class in Spring Boot for REST API
Write code to manually invoke garbage collection in Java
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