A hiring manager's question bank for experienced Python engineers. Use these to find the people who understand how Python actually executes, not just how to write a list comprehension.
Python is easy to write and hard to write well at scale, which is exactly what a senior interview should expose. Anyone can answer "what is a list comprehension" — the interesting questions are about what happens when the codebase grows: how the Global Interpreter Lock shapes your concurrency choices, why CPU-bound work needs multiprocessing while I/O-bound work fits threads or asyncio, and how a decorator or generator can either clarify or quietly break code that depends on it. A strong senior candidate has internalized that Python gives you a lot of rope, and can explain when they chose not to be clever. The questions below are grouped so you can probe the runtime, the language's functional features, real-world performance work, and the discipline that keeps a growing Python service maintainable — testing, typing, and clean API design. For a senior role, pair one GIL or concurrency question with one performance-profiling scenario and one design or API question; that combination separates engineers who have scaled Python in production from those who have only built scripts and small services. Look for candidates who reach for profiling before optimizing, who know when `asyncio` helps and when it just adds complexity, who treat type hints and tests as load-bearing rather than decoration, and who can describe a time they made a deliberately boring choice because it was the right one for the team.
Choose six to eight questions across two or three groups rather than rushing the full set. Push past first answers — when someone says "use multiprocessing," ask why, and when they'd be wrong to. Treat each question as the start of a conversation about trade-offs.
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