Welcoming questions
- Can you tell us about yourself and how you got into data engineering?
- Which data pipeline or platform you have built are you most proud of, and why?
Role-specific / technical competencies
- Walk us through the architecture of a pipeline you built end to end. What would you change today?
- How do you decide between batch and streaming for a new data source?
- How do you test data pipelines, and what does data quality monitoring look like in your current setup?
- Describe your approach to data modeling in a warehouse. When do you denormalize?
- A daily pipeline that feeds executive dashboards failed overnight. How do you handle the incident and prevent a repeat?
Behavioural & culture fit
- Tell us about a time analysts or scientists complained about data they depended on. How did you respond?
- Describe a situation where you pushed back on a request because it would create long-term technical debt.
- How do you keep stakeholders informed when a data issue affects their reports?
Problem-solving / case
- Warehouse costs doubled in a quarter with no obvious change in usage. How would you investigate and reduce them?
- We need to ingest data from a third-party API with unreliable uptime and shifting schemas. Design a robust approach.
- Two teams report different revenue numbers from the same warehouse. How do you find the source of the discrepancy and fix it for good?
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