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Commerce, Travel & Marketplaces

Uber

Mobility / marketplace · Data Engineering interview

SQL is decisive (window functions, marketplace metrics, late events), plus trips/payments modeling and real-time pipeline design.

Cloud / platform

Own infra + cloud; Spark, Hive, Kafka, Flink, Hudi, Presto

Reported difficulty

Not reported

SQLPythonSparkKafkaHudiData modeling

Hiring process

Recruiter

Tech screen (SQL + modeling)

Onsite (4–5)

Behavioral ownership

Hiring manager

Offer

Round-by-round breakdown

SQL & Analytics

· decisiveHigh confidence

Large event-driven datasets: joins, aggregations, window functions (PARTITION/LEAD/LAG)
Compute marketplace metrics; trends over time
Handle duplicate and late-arriving events

Data Modeling

High confidence

Design schemas for trips, users, payments, or events
Normalization trade-offs, SCDs
Support both batch and streaming consumers

Coding

Medium confidence

Problem-solving incl. DP-pattern; Spark concepts & programming

System & pipeline design prompts

Real-time marketplace analytics pipeline (Kafka → Hudi/Hive → Spark/Flink): late data, idempotency
Core metrics: GMV, take rate, driver utilization, rider cohort retention

Prep — high priority

SQL (window functions PARTITION/LEAD/LAG, marketplace metrics, late/dup events) — decisive
Data modeling (trips/payments/events, SCD, batch+streaming)
Real-time pipeline design

Prep — medium priority

Spark concepts
DP problem-solving
Behavioral ownership

Rejection patterns

Weak SQL performance is one of the most common reasons for rejection
Shallow data modeling
Cannot handle late/duplicate events
Weak pipeline reasoning

Reported experiences

Data Engineer

IllustrativeComposite

Composite from aggregator-reported questions: recruiter → tech screen (SQL + data modeling + pipeline reasoning) → onsite (SQL marketplace metrics + late events, trips/payments modeling, real-time pipeline design, behavioral ownership, HM).

Rehearse for Uber

Answered questions on what Uber actually asks — each with the short answer, the answer that gets you rejected, and the follow-up.

Then build one and have it reviewed: design a daily orders pipeline or model a marketplace. No account.

All interview experiences