Tell us about a data pipeline you designed or improved. What specific challenges did you face (e.g., scalability, latency, or data quality), and how did you solve them?
Describe a project where you optimized data performance or cost. What tools or strategies did you use, and what measurable results did you achieve?
Walk us through how you handled a major production issue in a data system. What caused it, how did you troubleshoot it, and what did you implement to prevent it from happening again?
Explain a time when you had to collaborate with non-data teams (e.g., business owners, marketing, finance, data scientists). How did you ensure alignment and communication across technical and non-technical stakeholders?
What’s one data architecture or design decision you’re most proud of? Why did you choose that approach, and how did it impact the project’s long-term scalability or maintainability?