Interview
Questions

Walk me through a data pipeline you designed from scratch. What were the key decisions you made, and what trade-offs did you consider?

Data quality issues can have significant downstream impacts. Describe a time you identified and resolved a data quality problem. How did you prevent it from recurring?

Data engineers often work closely with analysts and data scientists. Tell me about a time you collaborated with these stakeholders to understand and deliver their data needs.

Tell me about a time you had to handle data at significant scale. What challenges did you encounter, and how did you optimize for performance?

How do you decide between batch and streaming processing for a given use case? Describe a situation where you made this architectural decision.

Tell me about your approach to data modeling. Describe a complex data model you designed and the principles that guided your decisions.

Data pipelines fail. Tell me about a significant pipeline failure you dealt with. How did you respond, and what did you do to improve reliability?

Data engineering work often impacts business decisions. Describe a time you explained technical data concepts or limitations to non-technical stakeholders. How did you ensure understanding?

How do you approach testing for data pipelines and transformations? What strategies have you found effective for catching issues before they reach production?

Data infrastructure can be expensive. Tell me about a time you optimized data pipelines or storage for cost. What approaches did you take?

How do you handle schema changes and data migrations in production pipelines? Describe a challenging migration you managed.

Good documentation is crucial for data work. How do you approach documenting data sources, pipelines, and schemas? How do you help others discover and understand your data?

Data privacy and compliance are increasingly important. Tell me about a time you had to consider privacy requirements (GDPR, PII handling, etc.) in your data engineering work.

The data engineering ecosystem has many tools and frameworks. How do you evaluate and choose between different technologies for a project? Give a specific example.

What drew you to data engineering? What do you find most satisfying about building data infrastructure and enabling others to work with data?