314,552 interview questions from 6,000+ companies.
Approach for maintaining data quality and integrity across ETL pipelines.
Explain how you used a KPI and supporting metrics to diagnose a product issue and make a concrete product decision.
Investigate why a key KPI moved the wrong way after a product change and separate signal from noise.
Design a dashboard that connects campaign activity, funnel conversion, and acquisition efficiency to business outcomes.
Describe how you would evaluate a successful marketing campaign using funnel KPIs, conversion, and ROI.
Explain how to distinguish early directional metrics from outcome metrics, using a clear KPI framework tied to product decisions.
Approach for safely backfilling missing data while preserving correctness, idempotency, and data quality.
Explain what drives strong research work and how that motivation connects to user value and product outcomes.
Explain how to calculate cumulative totals in SQL using window functions, ordering, and optional pre-aggregation.
Design a pipeline for a real-time operational dashboard, covering streaming ingestion, modeling, data quality, and dashboard serving.
Define a North Star Metric for a product and explain how it guides KPI selection and growth decisions.
Framework for prioritizing new features in a mature product when engineering capacity is limited.
Choose sample size and runtime by combining baseline rate, MDE, alpha, power, and expected traffic.
Determine whether a metric change is explained by recurring seasonal patterns or by a true underlying shift.
Decide whether a metric move is statistically significant or just random variation.
Select a focused weekly growth metric set that balances top-line KPIs, leading indicators, and funnel visibility for leadership.
Identify whether a dashboard issue comes from the source data, workbook logic, or Tableau Server.
