Databricks Software Engineer Interview Questions

1.Tell me about a time you leveraged an open-source library or framework to solve a significant technical problem. What was the problem, which tool did you choose, and how did it impact your project?

2.Tell me about a time when you had to admit you didn't know something important in front of your team or stakeholders. What was the situation and how did you handle it?

3.Describe a time you identified a problem outside your immediate responsibilities and took action to fix it. What was the problem, why did you decide to tackle it, and what was the outcome?

4.Describe a time you contributed to or modified an open-source project to meet your team's needs. What changes did you make and how did you handle the contribution process?

5.Walk me through a project where you had tight deadlines but couldn't compromise on code quality. How did you approach the challenge and what specific practices did you use?

6.Tell me about a time you saw an inefficient process or system that wasn't your responsibility but was affecting your work. What did you do about it and what resistance did you encounter?

7.Write a function that efficiently finds all duplicate rows in a large DataFrame, considering that the dataset might not fit in memory on a single machine.

8.Implement a simple caching layer that can store and retrieve Spark DataFrame schemas with TTL expiration. The cache should be thread-safe and efficient for high-concurrency access.

9.Our Delta Lake implementation needs to optimize for both frequent small writes and large analytical queries. Walk me through how you'd design the file organization and compaction strategy.

10.You need to implement rate limiting for our MLflow model serving API that handles inference requests from thousands of models. How would you design this system?

11.You're designing a feature for Unity Catalog that needs to track data lineage across millions of tables and datasets. How would you design the storage and querying system for this lineage graph?

12.Design a system to automatically detect and alert on data quality issues across thousands of tables in a lakehouse, where each table might have different quality rules and SLA requirements.

13.Design a simple event streaming system that can capture real-time changes from Delta Lake tables and publish them to downstream consumers. Focus on the core architecture and delivery guarantees.

14.Design a monitoring system that tracks data pipeline health across thousands of Databricks jobs and notebooks. The system should detect failures, performance degradation, and data quality issues in real-time.

15.Design a metadata indexing system for Unity Catalog that can instantly search across millions of tables, columns, and their relationships. Users should be able to find relevant datasets within 100ms.

16.Build a system that automatically provisions and scales Databricks clusters based on incoming job queue depth and historical usage patterns. The system needs to minimize cold start times while controlling costs.

17.Design a system that can replicate Delta Lake tables across multiple cloud regions while maintaining ACID guarantees. The system needs to handle tables with millions of files and petabytes of data.

18.Build a system that manages experiment tracking for MLflow deployments across hundreds of data science teams. Each team runs thousands of experiments monthly, and the system needs to handle concurrent model training workloads.

19.Tell me about a time you had to convince a skeptical team to adopt a new technology or approach that you believed would benefit the project. How did you build consensus?

20.Describe a situation where you had to communicate a complex technical concept or system to non-technical stakeholders. How did you ensure they understood the implications?

21.Tell me about a time you had to choose between shipping a feature quickly to meet a deadline versus taking more time to build it properly. Walk me through your decision process.

22.Describe a time when you identified that your team was building the wrong solution for customers. How did you navigate changing course mid-project?

23.Tell me about a time you had to lead a technical decision that involved multiple teams with competing priorities. How did you achieve alignment and what was your role in the process?

24.Describe a situation where you had to mentor or guide someone more senior than you. What was the dynamic and how did you approach it?

25.Estimate how many Databricks workspaces are running Spark jobs at any given moment during peak business hours. Walk me through your assumptions and reasoning.

26.We're seeing 15% of MLflow model deployments fail during the first hour after deployment, but only 2% fail after 24 hours. What framework would you use to investigate this pattern?

27.Our Unity Catalog shows that data discovery queries have increased 300% but actual data usage has only grown 50%. What hypotheses would you investigate first?

28.A customer reports that their Delta Lake merge operations are taking 10x longer than expected. You have 30 minutes to gather information before a call with their team. What's your diagnostic approach?

29.Estimate the compute cost impact if we reduced cold start times for Databricks clusters from 3 minutes to 30 seconds across our customer base. How would you model this?

30.A major customer's data pipeline processes 500TB daily across 10,000 Delta tables, but they're hitting our API rate limits during peak hours. How would you design a solution that doesn't compromise other customers?