Databricks Staff Software Engineer Interview Questions

1.Tell me about a time you chose to use or contribute to an open-source project instead of building something proprietary. What drove that decision and what was the outcome?

2.Tell me about a time you identified a systemic inefficiency affecting multiple teams and took ownership of solving it. How did you build momentum and drive adoption?

3.Walk me through a time you saw a problem outside your team's area and decided to fix it yourself. What was the problem, how did you approach it, and what resistance did you encounter?

4.Tell me about a time when you disagreed with a popular technical decision and chose to voice your authentic opinion despite potential pushback. What happened?

5.Describe a recent project where you had to deliver high-quality software under significant time pressure. How did you ensure quality wasn't sacrificed for speed?

6.Walk me through your most significant open-source contribution. What problem were you solving, how did you engage with the community, and what was the long-term impact?

7.Design a REST API endpoint for MLflow Model Registry that allows teams to promote models from staging to production while ensuring proper governance and rollback capabilities.

8.Implement a Python function that efficiently reads from multiple Parquet files in parallel and applies a custom transformation while maintaining partition boundaries.

9.Write a function that efficiently merges streaming updates into a Delta table while handling late-arriving data and maintaining exactly-once semantics.

10.A customer's Spark job that processes 10TB daily has started failing with out-of-memory errors after a recent update. Walk me through your debugging approach.

11.You're implementing a feature in Delta Lake that requires maintaining ACID transactions while allowing concurrent reads and writes across thousands of partitions. How would you design the transaction coordination mechanism?

12.Our Unity Catalog service needs to handle permission checks for millions of data access requests per second across multiple cloud providers. Design the authorization architecture.

13.Design the streaming data ingestion pipeline that can handle 1 million events per second from customer Kafka clusters and write them to Delta tables with exactly-once semantics.

14.Design the experiment tracking backend for MLflow that needs to store metadata and artifacts for millions of ML experiments while supporting fast queries for model comparison and lineage tracking.

15.Design the auto-scaling system for Databricks clusters that can spin up 10,000 nodes in under 2 minutes when a customer submits a massive Spark job. What are the bottlenecks you'd need to solve?

16.Design the feature store backend for MLflow that needs to serve real-time features to thousands of model endpoints while also supporting batch feature computation jobs. How do you handle feature freshness guarantees?

17.Design the metadata synchronization system for Unity Catalog when it needs to replicate data lineage and governance policies across AWS, Azure, and GCP in real-time. How do you handle network partitions between clouds?

18.Design the job scheduler for Databricks workflows that needs to handle 100,000+ concurrent jobs across all customers while ensuring fair resource allocation and meeting SLA guarantees.

19.Tell me about a time you had to convince engineering leadership to adopt a technical approach that wasn't the obvious choice. How did you build the case?

20.Tell me about a time you mentored someone who was struggling with distributed systems concepts. How did you adapt your approach when your initial method wasn't working?

21.Describe a time you had to make a technical decision that would impact multiple product teams at Databricks scale. How did you ensure all voices were heard while still moving quickly?

22.Walk me through a time when a customer-facing issue required you to coordinate a response across multiple engineering teams. How did you ensure customer impact was minimized?

23.Describe a situation where you had to drive a major architectural change that required other teams to modify their existing code. How did you get buy-in and manage the transition?

24.Tell me about a time you identified a performance or scalability bottleneck that was affecting multiple teams but nobody owned. How did you drive a solution across organizational boundaries?

25.Delta Lake usage across our platform has grown 10x in the past year, but we're seeing customer complaints about query performance degrading. Estimate the key cost drivers and walk me through how you'd prioritize which optimization to tackle first.

26.A Fortune 500 customer wants to migrate 50PB from their legacy data warehouse to our lakehouse platform. Estimate the total migration timeline and identify the top 3 technical risks that could delay the project by 6+ months.

27.Our MLflow Model Registry is experiencing 20% higher latency during peak hours. Nothing changed in our deployment, but customer usage patterns have shifted. How would you diagnose what's causing the slowdown?

28.Estimate how many compute hours Databricks customers collectively use per month and what percentage of that is wasted due to idle clusters. Walk me through your reasoning and what this means for our product roadmap.

29.Unity Catalog adoption across our customer base has been slower than expected in certain industries. Estimate the revenue impact if we could increase adoption by 25% and outline the key barriers you'd investigate first.

30.We're considering open-sourcing a new component of our Photon engine. Estimate the engineering effort required and walk me through the key factors you'd evaluate to determine if this aligns with our Open Source First principle.