Technical Screening Questions for Backend Developers
Find backend engineers who can build robust, scalable systems. Use these 20 knockout questions to filter for database expertise, API design, and cloud deployment experience.
Why Screening Backend Developers is Hard
Hiring for backend roles is tough because the required skills are deep and complex. A resume might list "Python," "Java," or "Go," but this says nothing about a candidate's ability to design a scalable API, optimize a database query, or architect a resilient system. This often leads to senior engineers wasting valuable time in interviews with candidates who only have surface-level knowledge.
What to Look For in a Backend Developer
A strong backend engineer must have a deep understanding of databases (both SQL and NoSQL), API design principles (like REST), and a core programming language. For senior roles, look for experience with system design concepts like microservices, caching, and message queues. The best candidates can not only write code but also think about the reliability, scalability, and security of the entire system.
"The ability to filter for both SQL and NoSQL experience in 5 minutes is incredible. Sift is now our first step for all backend hires."
- Head of Platform, Fintech Startup
20 Knockout Questions for Backend Developers
| # | Question | Type | Knockout Rule |
|---|---|---|---|
| 1 | How many years of backend development experience do you have? | MCQ: 0-1 / 1-3 / 3-5 / 5+ | Below minimum = Knockout |
| 2 | Which backend language are you most proficient in? | MCQ: Python / Java / Node.js / Go / Ruby | Mismatch with stack = Knockout |
| 3 | Have you built REST APIs from scratch? | Yes / No | No = Hard Knockout |
| 4 | Have you worked with relational databases? (PostgreSQL, MySQL) | Yes / No | No = Knockout |
| 5 | Have you worked with NoSQL databases? (MongoDB, Redis, DynamoDB) | Yes / No | No = Knockout for NoSQL stacks |
| 6 | Have you written SQL queries independently? | Yes / No | No = Knockout |
| 7 | Have you implemented authentication systems? (JWT, OAuth) | Yes / No | No = Knockout for auth-heavy systems |
| 8 | Have you worked with message queues? (RabbitMQ, Kafka, SQS) | Yes / No | No = Knockout for async/event-driven systems |
| 9 | Have you worked with microservices architecture? | Yes / No | No = Knockout for distributed systems roles |
| 10 | Have you deployed backend services to cloud? (AWS, GCP, Azure) | Yes / No | No = Red flag |
| 11 | Have you used Docker for containerization? | Yes / No | No = Knockout for containerized environments |
| 12 | Have you worked with CI/CD pipelines? | Yes / No | No = Red flag |
| 13 | Have you written unit or integration tests? | Yes / No | No = Knockout for quality-focused teams |
| 14 | Have you handled database migrations in production? | Yes / No | No = Knockout for senior roles |
| 15 | Have you implemented caching strategies? (Redis, Memcached) | Yes / No | No = Red flag for performance-heavy systems |
| 16 | Have you worked with third-party API integrations? | Yes / No | No = Red flag |
| 17 | Do you have a GitHub profile or code samples to share? | Yes / No | No = Red flag |
| 18 | What is your expected salary range? | MCQ: Range bands | Out of budget = Knockout |
| 19 | What is your current notice period? | MCQ: Immediate / 2 weeks / 1 month / 2+ months | Mismatch = Knockout |
| 20 | Are you available for an interview within the next 7 days? | Yes / No | No = Deprioritize |
How to Use These Questions
Focus on your core stack. If you're a Python and PostgreSQL shop, make those your non-negotiable screening questions. Use a Sift quiz to ask about experience with building REST APIs, working with databases, and deploying to the cloud. This automated first pass ensures that every candidate who reaches a technical interview already has the foundational experience required, making your hiring process dramatically more efficient.
Common Screening Mistakes
A frequent mistake is focusing only on language proficiency while ignoring database and system design fundamentals. A developer who is great at Python but can't design a proper database schema is a liability. Another mistake is failing to screen for production experience; ask if they have deployed and maintained systems that real users depend on. These questions help you avoid those pitfalls.