Databricks Backend Developer Interview Questions (2026)

Landing a Backend Developer role at Databricks requires targeted preparation. Databricks interviews include coding rounds, system design sessions, and domain-specific discussions around data platforms. Engineering candidates face questions about distributed computing, Apache Spark internals, and lakehouse architecture. The company values technical depth, open-source contributions, and the ability to simplify complex data challenges for users. This guide covers the most frequently asked questions and insider tips to help you succeed in your Databricks Backend Developer interview.

About the Databricks Interview Process

Databricks interviews assess deep expertise in data engineering, distributed systems, and passion for democratizing data and AI.

Databricks interviews include coding rounds, system design sessions, and domain-specific discussions around data platforms. Engineering candidates face questions about distributed computing, Apache Spark internals, and lakehouse architecture. The company values technical depth, open-source contributions, and the ability to simplify complex data challenges for users.

Why Databricks Backend Developer Interviews Are Different

Databricks Backend Developer interviews differ from standard Backend Developer interviews in several key ways. The company has a unique interview culture, specific evaluation criteria, and expects candidates to demonstrate alignment with their values and mission. Understanding these differences gives you a significant advantage over other candidates.

Top 10 Backend Developer Interview Questions at Databricks

1. Databricks interviewers often ask: How would you design a rate-limiting system?
2. A common Databricks interview question: Explain the differences between REST and GraphQL.
3. Expect this at Databricks: How do you handle database migrations in production?
4. A common Databricks interview question: What is the CAP theorem?
5. At Databricks, you might be asked: Describe how you would implement authentication and authorization.
6. Databricks candidates should prepare for: How do you handle error handling and logging in a production system?
7. Databricks candidates should prepare for: What is the difference between horizontal and vertical scaling?
8. At Databricks, you might be asked: Explain microservices architecture and its trade-offs.
9. Databricks interviewers often ask: How do you secure an API endpoint?
10. Databricks interviewers often ask: Describe your experience with message queues and event-driven architecture.

Databricks-Specific Preparation Tips for Backend Developer Candidates

• Study Apache Spark architecture, distributed computing, and lakehouse concepts
• Prepare for system design questions involving data pipelines and analytics platforms
• Practice coding problems with focus on data manipulation and distributed algorithms
• Research the lakehouse paradigm and how it unifies data warehousing and data lakes
• Show knowledge of MLOps, data governance, and modern data stack trends

General Backend Developer Interview Tips

• Understand database design and normalization
• Practice designing scalable system architectures
• Know common security vulnerabilities and how to prevent them
• Be ready to discuss trade-offs in architectural decisions

Preparation Timeline for Databricks Backend Developer Interviews

• 4 weeks before: Research Databricks culture, recent news, and the specific team you are applying to.
• 2-3 weeks before: Practice technical questions daily and prepare behavioral stories using the STAR method.
• 1 week before: Do full mock interviews with HireFlow AI simulating Databricks interview style.
• Day before: Review your notes, prepare questions for the interviewer, and get a good night of rest.

Practice Databricks Backend Developer Interview with HireFlow AI — our AI adapts to Databricks's interview style and gives real-time feedback.