Lyft Data Engineer Interview Questions
The questions to prepare for a Lyft Data Engineer interview. Questions from real interview reports rank first. Updated weekly.
Find two ride fare values that reach a target using a hash map in O(n) time.
LyftFlatten a deeply nested JSON-like object into path-value pairs using recursion and deterministic key construction.
LyftAggregate per-city Lyft ride counts and fares in trailing time windows using queues and running totals.
LyftCalculate daily Lyft rider retention within the next 30 days using joins, aggregation, and ROW_NUMBER().
LyftTests SQL fundamentals for joining and reasoning about relationships between two tables.
LyftUse a CTE, aggregation, and window ranking to rank Lyft drivers within each city by weekly earnings.
LyftUse joins, a CTE, CASE logic, and date filtering to compute daily peak-hour acceptance rate for San Francisco ride requests.
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Discuss how you use data cataloging tools in pipelines, including metadata, lineage, data quality, and operational visibility.
LyftApproach for handling schema changes and data quality checks in a high-volume data lake pipeline.
LyftAssesses data modeling skills for Lyft’s driver-rider domain and ability to design for real-time and analytics.
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