Interview
Questions
Meta Data Engineering: Product Events and Reliable Data
Independent spoken practice for product data engineering: event definitions, data models, privacy, infrastructure trade-offs, and production reliability. Informed by public role descriptions and a dated engineering example; not an official Meta interview guide.
Practice these questions directly. An editable copy is yours to change; the original stays unchanged.
Walk me through a data pipeline you designed from scratch. What were the key decisions you made, and what trade-offs did you consider?
Facebook and Instagram teams count the same interaction differently, and a new mobile release changes the logged fields. How would you agree on an event definition, evolve the schema, and check that the resulting product metrics remain comparable?
Tell me about your approach to data modeling. Describe a complex data model you designed and the principles that guided your decisions.
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.
Your Meta ads-ranking team proposes a feature that improves offline prediction but greatly increases event storage and pipeline latency. How would you assess the end-to-end trade-off and decide what to build or change?
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?