Databricks Engineering Manager Interview Questions

1.Describe a situation where you saw a problem outside your team's scope but took ownership to fix it anyway. What was the problem and what did you do?

2.Tell me about a time when you had to share difficult feedback or admit a mistake in a high-stakes situation. How did you approach it and what was the outcome?

3.Tell me about a time you advocated for using or contributing to an open-source solution when your team wanted to build something proprietary. What was the business problem and how did you make your case?

4.Describe a time when you had to choose between building an internal tool versus adopting an existing open-source solution. What factors did you consider and what did you decide?

5.Walk me through a time when you had to deliver a high-quality product under an aggressive timeline. How did you ensure quality didn't suffer while meeting the deadline?

6.Tell me about the most significant process or system improvement you drove that was outside your direct area of responsibility. What made you take ownership and how did you get buy-in?

7.A customer reports that their Spark jobs on Databricks are failing with OutOfMemory errors when processing 100TB+ datasets. How would you systematically troubleshoot this?

8.Design a simple in-memory cache for Delta Lake file metadata that can handle 10M+ files with automatic eviction. What data structures would you use and why?

9.Our Unity Catalog service is experiencing metadata query latencies that spike to 5+ seconds during peak hours when hundreds of thousands of tables are being accessed. Walk me through how you'd diagnose and fix this.

10.Write a function that efficiently finds all Delta Lake table dependencies in a workspace where tables can reference each other through views, streaming jobs, and ML pipelines. The workspace has 50,000+ tables.

11.A product team wants to add real-time feature serving to MLflow Model Serving, but our current Delta Lake-based architecture has 30-second refresh latencies. How would you evaluate whether to build this capability?

12.You need to design the schema versioning system for Delta Lake tables that may have thousands of columns and millions of partitions. What are the key challenges and how would you solve them?

13.Design a job scheduling system for Databricks workflows that can handle 100,000+ concurrent jobs with complex dependencies. How do you ensure fair resource allocation across different customers?

14.Design the metadata synchronization system for Delta Lake tables that span multiple cloud regions. How do you handle consistency when network partitions occur?

15.Design a feature store for MLflow that needs to serve both batch and real-time feature requests. The system should handle 50,000+ features with sub-100ms latency for online serving.

16.Design the permission evaluation system for Unity Catalog that needs to check data access rights across millions of objects with complex inheritance patterns. How do you keep authorization checks under 10ms?

17.Design the lineage tracking system for Unity Catalog that can track data dependencies across 100,000+ tables, views, and ML models in real-time. How would you handle the scale and ensure queries remain fast?

18.Our Spark cluster autoscaling system needs to handle workloads that can scale from 10 to 10,000 nodes in under 2 minutes. How would you design the orchestration layer to make this reliable?

19.Tell me about a time when you had to convince leadership to invest in technical infrastructure that wouldn't show immediate customer value. How did you make the case?

20.Tell me about the most complex cross-team engineering initiative you've led. How did you handle coordination when teams had competing priorities?

21.Describe a time when your team's approach to solving a customer problem differed significantly from what the product team originally envisioned. How did you navigate that tension?

22.Tell me about a time when you had to make a significant architectural decision that would affect multiple teams, but you couldn't get consensus. How did you move forward?

23.Describe a situation where you inherited an underperforming senior engineer who other teams had lost confidence in. What did you do?

24.Walk me through a time when you successfully influenced a director or VP-level leader to change their technical strategy. What was your approach?

25.Estimate how many Delta Lake tables get created across all Databricks workspaces globally in a typical month. Walk me through your reasoning and key assumptions.

26.Our MLflow Model Registry is seeing a 40% increase in model deployment requests, but inference latency is staying flat. What operational metrics would you track to understand if this is sustainable growth or if we're heading toward a performance cliff?

27.A Fortune 500 customer wants to migrate 50,000 Hive tables to Delta Lake format on Databricks, but they need zero downtime and can't afford data inconsistencies. How would you estimate the engineering effort and timeline for building the migration tooling?

28.Unity Catalog adoption is growing 200% quarter-over-quarter, but our customer success team reports that 30% of trials don't convert because setup complexity is too high. How would you prioritize which onboarding friction points to fix first?

29.Databricks is considering building a native vector database for AI workloads versus integrating with existing solutions like Pinecone or Weaviate. How would you structure the analysis to recommend whether to build or partner?

30.Our Photon engine team claims their new vectorized query optimization can improve customer workload performance by 3x, but it requires 6 months of engineering work and carries some backwards compatibility risks. How would you evaluate whether this is the right investment for Databricks?