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DoorDash interview practice

DoorDash Code Craft interview and technical practice. Start with verified evidence.

Practice from 19 DoorDash-tagged public coding problems, organized only by the stage, topic, difficulty, and recency metadata FastPrep can verify. The broader public catalog also includes 6 system-design exercises, 4 project-coding exercises.

Catalog
29 public practice assets (19 coding)
Start here
Use the stage named in your invitation
Evidence
OA · Phone · Onsite metadata, shown in context
DoorDash practice workspace
Stage-led · public FastPrep catalog

Phone practice path

Phone Screen

Practice solving while explaining assumptions, tradeoffs, and complexity. Problems are ranked by repeated public catalog sightings.

Solve one end to end

8 DoorDash-tagged Phone Screen problems available.

CompanyProblemDifficultyPublic evidenceAction
DODoorDash
Dasher Pay with Store Waits and Peak HoursHash TableSimulationMedium
11 public reportsLast reported Oct 2026
Practice
DODoorDash
Customer Bootstrap APIDesignSimulationMedium
6 public reportsLast reported Sep 2026
Practice
DODoorDash
Closest DashMartMatrixBreadth-First SearchMedium
2 public reportsLast reported Jul 2026
Practice
DODoorDash
Dasher Active TimeArraySimulationMedium
1 public reportLast reported Sep 2026
Practice
DODoorDash
Merchant Capacity Interval MergeArrayHash TableMedium
1 public reportLast reported Aug 2026
Practice
DODoorDash
Open Restaurants in a City RangeArrayGeometryEasy
1 public reportLast reported Aug 2026
Practice
DODoorDash
Maximize Total Profit by Assigning Chefs to DishesGreedySortingMedium
1 public reportLast reported May 2026
Practice
DODoorDash
Return Priority of Order IDsArrayHeapMedium
1 public reportLast reported Jun 2025
Practice

Current official guidance

How DoorDash describes its current AI-assisted session.

DoorDash's March 2026 engineering article describes a 60-minute AI-assisted working session in the candidate's own environment. Candidates often search for this topic as Code Craft, but the official article does not use that name; follow the wording and rules in your invitation.

Primary sources checked .

  • The session uses starter code or a practical task and allows an integrated AI assistant in the candidate's own environment.
  • DoorDash says it evaluates orientation, verification of AI output, debugging, scoped changes, and communication—not just whether code runs.
  • Other rounds can have different tool rules, so recruiter guidance and the invitation remain the source of truth.

01 · Stage workflow

Rehearse Code Craft as a working session.

Use the verified live practice inventory to rehearse orientation, debugging, testing, bounded changes, and tradeoff narration without claiming to reproduce a DoorDash interview. Your invitation and recruiter guidance remain the source of truth.

  1. 01

    Online Assessment

    Use the timing and format in your invitation as the source of truth. In practice, work without interruptions, budget time to read constraints, and reserve a final review window for boundary cases.

    • State the input, output, and complexity target before coding.
    • Implement one complete solution inside a fixed timebox.
    • Run small, duplicate, empty, and boundary cases before finishing.
  2. 02

    Phone Screen

    Treat the problem as a conversation. Clarify the contract, describe the approach before implementation, and keep narrating meaningful decisions while you code and test.

    • Ask clarifying questions instead of silently filling gaps.
    • Explain the data structure and expected complexity.
    • Walk through at least one example and one edge case aloud.
  3. 03

    Onsite

    Use the catalog's onsite labels as practice context, not as a promise about a specific loop. Focus on collaborative problem solving: compare approaches, implement cleanly, and explain how the solution behaves at scale.

    • Compare a straightforward approach with the optimized one.
    • Keep the implementation readable while discussing tradeoffs.
    • Test the result, then name follow-up improvements explicitly.

02 · Broader technical practice

Practice beyond standalone coding questions.

These public DoorDash-tagged exercises cover additional technical formats. They are included only when a verified catalog record and a crawlable practice page both exist.

System designLast seen Oct 2026

Food Review System

Design item-level ratings and reviews for a food-delivery menu, including verified purchasers, switchable votes, low-latency browse projections, and exactly-once reviewer rewards at configurable upvote thresholds.

Open practice
System designLast seen Oct 2026

Design a Scheduled Job Execution System

Design a durable one-time and recurring job service with stable occurrence identity, at-least-once execution safety, and private object-storage logs for every run.

Open practice
System designLast seen Oct 2026

Design an Ad Event Measurement Platform

Design a reliable event-time pipeline that ingests ad events and serves reproducible campaign analytics despite duplicates, late data, and replay.

Open practice
Project codingLast seen Sep 2026

Build a Refund DAG with Local HTTP Services

Implement a continuously running refund workflow DAG with distinct local HTTP services, automatic late-order refunds, partial refunds, and asynchronous slow execution.

Open practice
Project codingLast seen Sep 2026

Debug Two Routing Strategies

Repair broken round-robin and consistent-hash routing implementations and verify the result.

Open practice
Project codingLast seen Sep 2026

Integrate Three Profile Services

Complete a resilient profile bootstrap API that joins consumer, payment, and address data across distinct identifiers.

Open practice
Project codingLast seen Sep 2026

Build a Dasher Payout Service

Build a payout endpoint that looks up a Dasher's deliveries and calculates dollar pay from active delivery minutes, including overlapping deliveries.

Open practice
System designLast seen Aug 2026

Design a Sliding-Window Restaurant Leaderboard

Design a seconds-fresh top-ten restaurant leaderboard over a sliding one-hour order window.

Open practice
System designLast seen Aug 2026

Design a Downstream-Service Alert Notification System

Design a message-queue-backed platform that routes durable alerts to subscribed services with isolated retries, replay, and backpressure.

Open practice
System designLast seen Jul 2026

Design a Three-Day Charity Event System

Design registration, capacity control, and check-in for activities and volunteer shifts across a three-day charity event.

Open practice

03 · Evidence boundary

What “DoorDash interview questions” means here.

It means practicing transferable implementation, testing, and technical reasoning with public catalog assets FastPrep tags to DoorDash. It does not mean FastPrep has access to the company's assessments or any private interview bank.

Repeated public sightings and last-reported dates can help you prioritize practice, but they cannot predict the questions, format, or platform in a specific interview.

  • Only DoorDash-tagged FastPrep catalog problems appear above.
  • Stage labels and report dates remain visible as context.
  • No official, private, leaked, or proprietary questions are claimed.

04 · Plain answers

DoorDash interview practice questions, answered plainly.

This page owns technical-practice intent for DoorDash. Hiring activity, timelines, and market signals remain on the separate hiring-insights page.

01Does DoorDash officially call this interview Code Craft?

No official source reviewed for this page uses Code Craft as the format name. DoorDash's March 2026 article describes a 60-minute AI-assisted engineering working session. FastPrep maps the candidate search term to transferable practice. FastPrep currently links 4 DoorDash-tagged project-coding exercises. Your invitation remains the source of truth for the current name, tools, and rules.

02Is FastPrep affiliated with DoorDash?

No. FastPrep is an independent interview-preparation product and is not affiliated with DoorDash. The page uses FastPrep's public practice catalog and does not claim official, private, leaked, or proprietary employer questions.

03How are DoorDash problems assigned to interview stages?

Stage labels come from FastPrep's public problem metadata. A problem can carry more than one reported stage, and hiring processes can change by role, level, location, and date. Treat the labels as preparation context, not a guarantee.

04Which DoorDash interview stage should I practice first?

Start with the stage named in your invitation or recruiter message. If no stage is known, use the largest available set to build general problem-solving fluency, then rehearse explanation and testing separately.

05Does this page predict the DoorDash interview process?

No. Public catalog counts, stage tags, and last-reported dates can help prioritize practice, but they cannot predict a specific interview's questions, sequence, timing, or platform.

Your next stage, made concrete

Pick a problem. Solve it end to end.

Start with the stage named in your invitation, then use public evidence as context—not as a promise of what you will be asked.

Open the practice set