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Keepler Interview Questions

The questions to prepare for Keepler interviews, across all roles. Questions from real interview reports rank first. Updated daily.

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1
SQL & Data ManipulationStart here. 7 questions + 1 drill · ~76 min
Rolling Average Over Last 30 DaysMedium
Practice

Calculate each customer's 30-day rolling engagement average using a PostgreSQL window function.

Date FunctionsData ManipulationAggregationsKeepler
SQL: First and Last Event Per UserMedium
Practice

Use ranked window functions and conditional aggregation to identify each NewWave user’s first and last recorded event.

Window FunctionsDate FunctionsRankingKeepler
Ensuring Integrity Across Data SourcesEasy

Explain practical SQL techniques to preserve data integrity when combining multiple data sources.

JoinsData WranglingCase WhenKeepler
Consecutive Activity Days QueryMedium
Practice
Practice drill

Identify each user's consecutive website activity streaks using date arithmetic and SQL window functions.

Window FunctionsDate FunctionsData ManipulationIntuit Management ConsultancyChewySuperhuman
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2
Behavioral & Leadership7 questions · ~66 min
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3
More topics5 questions · ~47 min
Statistical Significance in Hypothesis TestingEasy

Explain what statistical significance means and why it matters when interpreting experimental or analytical results.

Hypothesis TestingData AnalysisStatistical SignificanceKeepler
Diagnose Engagement DropHard

Identify the causes of a quarterly engagement decline through metric validation, decomposition, segmentation, and trend analysis.

MetricsDiagnosisuser engagementKeepler
Measure New Dashboard Feature SuccessMedium

Define a framework to measure whether a new observability dashboard feature is delivering real value and sustained adoption.

Feature PrioritizationUser NeedsProduct VisionKeepler
Experiment Design for a Mobile AppHard

Design a mobile feature A/B test with clear hypotheses, metrics, MDE, power, randomization, analysis, and shipping criteria.

experiment designMDEmobile appKeepler
Investigate Sudden Metric DropHard

Build a systematic process to validate a 10% overnight KPI decline, isolate its cause, and recommend corrective action.

root cause analysisKPIoperational healthKeepler

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