Backend Language Proficiency Questions

Demonstrate strong practical knowledge of a backend programming language such as JavaScript with Node dot js, Python, Java, Go, or similar. Cover language fundamentals, idiomatic usage, standard library features, package and dependency management, common frameworks and ecosystem tools, testing strategies and tooling, error handling and observability, and patterns for maintainable server side code. Be ready to explain concurrency and asynchronous models in the language, performance considerations, security best practices, deployment and packaging approaches, and examples of backend services or APIs you built including trade offs and chosen libraries.

MediumTechnical

65 practiced

Describe best practices for error classification and handling in backend ETL services (choose Java or Python). Cover retry policies (idempotent vs non-idempotent), exponential backoff, poison message handling, logging context without leaking secrets, and mapping failure types to alerting thresholds.

EasyTechnical

43 practiced

Compare processes vs threads regarding memory isolation, inter-process communication cost, scheduling, and fault isolation. In Python, explain the difference between threading.Thread and multiprocessing.Process and when you'd use each in a data ingestion worker. Include the effect of the GIL on CPU-bound vs I/O-bound workloads.

EasyTechnical

39 practiced

Explain the differences between var, let, and const in JavaScript / Node.js. In your answer include scoping rules (function vs block), hoisting behavior, reassignment, and typical idiomatic usage on the backend. Give a short code example showing a pitfall with var that let/const avoid and describe the fix.

EasyTechnical

42 practiced

You are implementing a merge step in a data pipeline that merges two sorted lists of integers. In Python, write a function `merge_sorted(list1, list2)` that returns a new sorted list without calling the built-in sort. The function should run in O(n + m) time and use O(1) extra list allocations beyond the output. Context: this will be used to merge two sorted partitions produced by a map stage. Provide sample input and expected output.

HardTechnical

43 practiced

A Python service parsing large JSON payloads per request shows high CPU and latency at production load. Explain how to profile CPU and memory (py-spy, cProfile, sampling flamegraphs), interpret results, and propose optimizations: switch to orjson, stream parse with ijson, offload parsing to worker processes, or move hot path to a compiled language. Provide commands and a recommended mitigation plan.

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