Doordash Data Analyst Interview Guide

DoorDash Data Analyst reports point to timed SQL work and decision-focused analysis. Candidates describe SQL questions involving grouping, customer order-frequency segmentation, restaurant sales trends, month-over-month calculations, quartiles, CTEs, LAG, and updating an existing query. One report describes four questions under tight time limits, while another emphasizes the need to clarify ambiguous requirements before writing a query. Practice explaining your interpretation concisely, then structure queries so you can check them quickly.

Case work is a major part of the reported process. Candidates mention an offline take-home, a live discussion of the work, and open-ended prompts on success metrics, experiment design, diagnostics, and strategic recommendations. One case asked for an explanation of differing customer complaints across fulfillment approaches. Build a clear narrative: define the business question, identify the metric, explain the analysis, and connect findings to an action.

Behavioral conversations can include a hiring manager, peers, team members, and cross-functional partners. Expect follow-up questions about your background, SQL experience, judgment, and how you communicate analytical work. Reported sequences vary, so treat the exact number and order of interviews as team-dependent.