Backend Developer Role Questions

Demonstrate clear knowledge of the backend developer position, including core responsibilities and the technology choices that commonly support them. Topics include designing application programming interfaces, service and data models, database design and query optimization, authentication and authorization strategies, scalability and performance trade offs, reliability and observability practices, security considerations, test strategies for backend code, deployment pipelines and release workflows, and familiarity with common runtime platforms and infrastructure such as Node.js, Python, Java, PostgreSQL, MongoDB, Amazon Web Services, and Microsoft Azure. Candidates should also be able to ask targeted questions about existing architecture, integration points, expected throughput and latency, operational responsibilities, and the team ownership model.

HardTechnical

82 practiced

Describe and sketch an implementation for a strongly consistent distributed token-bucket rate limiter used across N stateless API servers. The solution must avoid race conditions and provide low-latency checks. Compare a central Redis-based approach (with Lua scripts), a Redis cluster with sharded keys, and a decentralized/gossip-based approach. Discuss availability and latency trade-offs and how to handle Redis failover safely.

MediumSystem Design

61 practiced

Design a background processing system for image-processing tasks with the following requirements: reliable delivery (at-least-once), retry with exponential backoff and jitter, dead-letter handling for poison messages, idempotent workers, prioritized queues, and autoscaling workers. Choose between SQS, RabbitMQ, and Kafka and justify your choice. Sketch worker lifecycle, how to handle retries and DLQs, and how to monitor backlog and processing latency.

MediumTechnical

61 practiced

Design a caching strategy for a product catalog service with heavy reads and infrequent writes. Compare cache-aside, write-through, and write-back policies. Recommend a strategy considering cache invalidation, TTL, stale reads, and cold starts. Also describe how you'd use Redis (clustering, persistence settings) in production and how to mitigate cache stampede.

HardTechnical

65 practiced

During a production incident you observe a sudden increase in p95 latency for a key API endpoint. Describe a runbook-style investigation: which dashboards and metrics to check first (CPU, GC, DB latency, queue length), how to use distributed tracing to locate hotspots, how to correlate traces with logs to find root cause, and what temporary mitigations (circuit breaker, rate limiting, limiting features) you would deploy while fixing the root cause. Also describe post-incident verification steps.

MediumTechnical

63 practiced

Explain optimistic vs pessimistic locking and when to use each. Then provide code (in Java or Python) demonstrating optimistic locking for updating product inventory using a 'version' integer column: read the row, check the version, update where id and version match, and handle retry on conflict. Specify transaction boundaries and backoff strategy for retries.

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