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Prep plan
Updated weekly · Last refresh Aug 30

Stubhub Data Analyst Interview Questions

The questions to prepare for a Stubhub Data Analyst interview. Questions from real interview reports rank first. Updated weekly.

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1
SQL & Data ManipulationStart here. 7 questions + 3 drills · ~86 min
Window Ranking in Ticket QueuesMedium

Explain SQL window functions and when to use ROW_NUMBER() versus DENSE_RANK() for ranked ticket analysis.

Window FunctionsRankingrow_numberStubhub
Explain Full Outer vs Left JoinMedium

Explain how FULL OUTER JOIN and LEFT JOIN differ when reconciling customer records across systems.

JoinsData WranglingCase WhenStubhub
Optimize Clickstream AggregationsHard

Tests performance tuning for large-scale event data and query optimization.

Performance TuningAggregationsStubhub
SQL Role and TheoryMedium

Tests understanding of SQL concepts and how they underpin data analysis work.

role expectationssqlStubhub
Normalized vs Denormalized for BIMedium

Tests data modeling tradeoffs for BI performance, maintainability, and correctness.

normalizationData ModelingStubhub
SQL Nth Highest Salary QueryEasy
Practice
Practice drill

Find the third-highest distinct employee salary using PostgreSQL DISTINCT, ORDER BY, LIMIT, and OFFSET.

sql queryRankingsalaryPaytmEEPAM IndiaBoston Consulting Group
Contact Center Agent Performance MetricsHard
Practice
Practice drill

Compute daily agent call KPIs and SLA using joins, aggregations, and window ranking in a contact center model.

ETLAggregationsData ModelingADP
Monthly Sales Trends by CategoryMedium
Practice
Practice drill

Aggregate monthly sales by product category and use LAG to calculate month-over-month changes.

InfrastructureToolsData WranglingTotal Wine & MoreInc.Benjamin Moore
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2
Behavioral & Leadership8 questions · ~64 min
Resolving Data Quality Under PressureMedium

Tests ownership of data quality issues, risk communication to leadership, and stakeholder management under business pressure.

Data QualityCommunicationLeadershipStubhub
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3
More topics2 questions · ~16 min
Data Quality in ML PipelinesMedium

Practical approach for maintaining data quality across ML ETL pipelines, orchestration, and repeatable data processing.

Data QualityETLData ModelingStubhub
dbt vs Raw SQL ScriptsMedium

Tests understanding of modern transformation tooling, maintainability, and workflow design.

transformationsOrchestrationStubhub

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The finish line: interview-readyComplete all 17 questions plus 3 hands-on drills to finish this plan.