314,552 interview questions from 6,000+ companies.
Approach for maintaining data quality and integrity across ETL pipelines.
Design a dashboard that connects campaign activity, funnel conversion, and acquisition efficiency to business outcomes.
Explain how to distinguish early directional metrics from outcome metrics, using a clear KPI framework tied to product decisions.
Explain how INNER JOIN and LEFT JOIN differ, and when to use each for matched-only versus all-left-row analysis.
Approach for safely backfilling missing data while preserving correctness, idempotency, and data quality.
Explain what a p-value means in hypothesis testing and how it relates to statistical significance.
Compare ETL and ELT, and explain when ELT is the better pipeline pattern.
Analyze where users drop off in a product funnel and identify the biggest conversion leak.
Explain SQL window functions and when to use ROW_NUMBER() versus DENSE_RANK() for ranked ticket analysis.
Tests SQL reasoning under strict constraints and ability to compute rankings without aggregates.
Approach for adding data quality checks, observability, and production monitoring to a data pipeline.
Explain how to evaluate whether an A/B test result is statistically significant and how to interpret the result.
Define the metrics that show whether engagement in a core feature is improving.
Explain why correlation measures association, while causation requires evidence that changing one variable changes the other.
Tests your performance troubleshooting skills for dv01-scale reporting queries.
Explain how INNER JOIN and LEFT JOIN affect missing records and when to use each while debugging data mismatches.
Reason about power analysis when planning an experiment and choosing sample size.
Explain how LEFT JOIN vs INNER JOIN changes report completeness, NULL handling, and KPI interpretation in Meta-style reporting.
Explain how to structure a cohort retention query using cohort assignment, period offsets, and aggregation in PostgreSQL.
Explain INNER JOIN vs LEFT JOIN semantics, NULL behavior, and common pitfalls (filters turning LEFT into INNER) using real analytics examples.
23 total questions
