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

0 practiced

Design a testing strategy and CI pipeline for a Python data ingestion microservice. Cover unit tests, integration tests against ephemeral databases (Docker/testcontainers), contract tests for downstream consumers, and end-to-end acceptance tests. Explain test-data management, seeding, and approaches to reduce flakiness in integration tests.

HardTechnical

0 practiced

A Python job crashes with RecursionError while processing deeply nested JSON (depth > 2000). Implement an iterative DFS or explicit-stack-based parser function that flattens nested objects into dot-notated keys and values without recursion. Explain Python recursion limits and why tail-call elimination is not available in CPython.

HardTechnical

0 practiced

Given a service that writes business data to a transactional relational database and also publishes events to an asynchronous analytics sink (Kafka), design a reliable approach that avoids data loss and limits duplicates. Explain the transactional outbox pattern, CDC approaches (Debezium), and idempotent consumers. Provide pseudocode for writing the outbox and for a publisher that guarantees at-least-once delivery with idempotent consumer semantics.

MediumTechnical

0 practiced

Compare dependency management strategies for Go (go modules) and Java (Maven/Gradle). Discuss module versioning, reproducible builds, vendoring, handling transitive dependencies, and mitigating transitive vulnerabilities. Which approach best reduces surprises in production builds and why?

EasyTechnical

0 practiced

Explain how to manage Python project dependencies for reproducible deployments. Describe and contrast virtualenv + requirements.txt, pipenv, poetry, and using Docker. Show an example requirements.txt snippet and explain how to pin versions and produce a lockfile for production builds.

Unlock Full Question Bank

Get access to hundreds of Backend Language Proficiency interview questions and detailed answers.

Join thousands of developers preparing for their dream job.