Netflix Business Context & Data Engineering Role Questions
Understanding Netflix's business model, product strategy, and organizational context, with a focus on the Data Engineering role. Covers how Netflix operates in streaming, content recommendations, data platforms, and data engineering responsibilities, including data pipelines, platform architecture, and how business goals drive data work within Netflix.
MediumTechnical
0 practiced
Explain counterfactual policy evaluation (CPE) and how you would apply it to estimate the offline impact of a new ranking policy at Netflix using logged bandit feedback. Include descriptions of IPS, SNIPS, direct method, doubly robust estimators, and main assumptions and limitations.
MediumSystem Design
0 practiced
Design a data platform for Netflix that must support both high-throughput streaming analytics (1B events/day) and large-scale batch reporting (petabytes of storage). Outline the components (ingestion, stream processors, storage tiers, warehouses, serving layers), data contracts, durability and scaling strategies, and how you would separate concerns to allow many teams to build safely on the platform.
EasyTechnical
0 practiced
Explain the basic process of running an A/B test for a UI change on Netflix's landing page. Include: hypothesis formation, choosing primary and guardrail metrics, randomization strategy, sample size / power estimation, running the experiment, and a short checklist for interpreting results safely.
MediumTechnical
0 practiced
You have two large tables:playback_events(event_id, user_id, title_id, watch_seconds, ts)catalog(title_id, genre, release_year)Write an optimized SQL query to compute the top 10 genres by average watch_seconds in the last 90 days. Explain partitioning/indexing strategies, join strategies, and how to handle skew and late-arriving data.
EasyBehavioral
0 practiced
Netflix emphasizes culture principles like 'freedom and responsibility' and 'context not control.' Describe a time (or propose a detailed hypothetical scenario) in which you, as a Data Scientist, balanced autonomy with delivering business-aligned results. Use the STAR (Situation, Task, Action, Result) format.
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