
Netflix
Senior
Own foundational data pipelines for Netflix's first EMEA Data Engineering teams (Enterprise Data or Member Data Engineering)
Netflix is standing up its first Data Engineering presence in EMEA (Warsaw) across two tracks — Enterprise Data (consolidating 500+ internal apps like Jira/Slack/Zendesk into decision-ready data products) and Member Data Engineering (client/server logging and A/B-testing data behind Netflix's recommendation product experience). The role wants 6 years of batch/real-time pipeline experience, Python/Scala plus complex SQL, data modeling for warehouse-scale reporting, and mentoring ability. Expect the mock to focus on pipeline ownership, data modeling tradeoffs, and translating ambiguous business asks into engineering work — this is senior IC scope, not people management.
Step into this interview
Free · a live voice mock calibrated to this exact role
What this interview tests
- End-to-end batch and real-time pipeline ownership at scale
- Data modeling for warehouse reporting and fast retrieval
- Python/Scala plus complex SQL for orchestration and ad-hoc analysis
- Translating ambiguous business requirements into data engineering deliverables
- Mentoring and cross-functional partnership with data scientists/product managers
Common question themes
Describe owning a data pipeline end-to-end — from stakeholder ask to production table
How would you decide between a batch and a real-time pipeline for a new data source
Walk through modeling data from an application API or event stream for analytics use
Tell me about a time you turned an ambiguous business question into a concrete data requirement
How have you mentored engineers who were navigating unclear or shifting requirements
Related interviews

Netflix
Senior
Integrations Support Engineer 5 - Ads Conversion API

Netflix
Senior
Software Engineering 5 - Ads Conversion Attribution

Netflix
Senior
Software Engineer 5, Ads Reporting

Dropbox
Staff
Staff Data Engineer, Analytics Data Engineering

Airbnb
Senior
Senior Data Engineer, People Analytics

Amazon
Mid