Data Analyst interview
at Google.

Tell-me-about-a-time stories on ownership, conflict, and impact — scored against this company's real values.

1. 01 Tell me about a time you turned a messy, ambiguous dataset into a clear recommendation that influenced a decision.
2. 02 Describe a situation where you had to explain a complex analysis to a non-technical stakeholder and drive action.
3. 03 Tell me about a time your analysis contradicted what the team expected, and how you handled the pushback.
4. 04 Describe a project where you had to balance speed and rigor under a tight deadline.

The hard screen for the craft itself — talked through out loud, not whiteboarded in your head.

1. 01 Write a SQL query using ROW_NUMBER() to find the top three most active users per day from an events table.
2. 02 Given a funnel of sign-up steps, write SQL to compute the drop-off rate between each consecutive step.
3. 03 How would you decide whether an observed conversion increase is real or just noise, and what would you compute?
4. 04 Write a query to identify users whose activity dropped to zero after previously being daily active, handling NULLs correctly.

Open-ended design of the systems this company actually runs, with the interviewer probing your tradeoffs.

1. 01 Design the dashboard and metric definitions to monitor daily and monthly active users for Google Maps.
2. 02 Design a reporting pipeline to track and explain engagement trends across YouTube creators.
3. 03 Define and design how you'd measure the success of a new Google Search results feature end to end.
4. 04 Design a self-serve metrics layer that lets product teams reliably query Gmail engagement data without inconsistent definitions.