Hiring senior backend engineers requires probing beyond basic syntax and CRUD endpoints. Senior engineers must demonstrate mastery over database indexing, distributed locking, message queues, rate limiting, and failure mitigation.
Database & Data Persistence
1. How do B-Tree indexes work, and when can an index degrade write performance? *Expected Answer*: B-Trees allow logarithmic O(log N) search lookups. However, every inserted or updated row requires updating associated indexes, increasing write latency and storage overhead. 2. Explain the difference between Optimistic and Pessimistic Locking. 3. How do you detect and resolve N+1 database query issues? *Practice the N+1 Queries exercise on Pairlet.*
Caching & Concurrency
4. How do Cache-Aside, Write-Through, and Write-Behind caching strategies differ? 5. How do you implement an LRU (Least Recently Used) cache? *Try the LRU Cache problem on Pairlet.* 6. How do you prevent Cache Stampedes (Thundering Herd Problem)?
Message Queues & Distributed Systems
7. How do At-Least-Once vs At-Most-Once delivery guarantees impact message consumer design? 8. What is an Idempotency Key, and how do you implement it in API gateways?
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Frequently Asked Questions
What sets a senior backend engineer apart in technical interviews?
Senior backend engineers focus on system trade-offs, failure modes, data consistency, observability, and long-term maintainability rather than just making code pass happy-path unit tests.
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