System designLast reported Sep 2026
Food Review System
Design a food-review service that accepts verified customer reviews, lets readers vote on other users' reviews, and serves trustworthy restaurant summaries and review pages.
Open practiceDoorDash interview practice
DoorDash Code Craft interview and technical practice. Start with verified evidence.
Practice from 17 DoorDash-tagged public coding problems, organized only by the stage, topic, difficulty, and recency metadata FastPrep can verify. The broader public catalog also includes 5 system-design exercises, 3 project-coding exercises.
- Catalog
- 25 public practice assets (17 coding)
- Start here
- Use the stage named in your invitation
- Evidence
- OA · Phone · Onsite metadata, shown in context
OA practice path
Online Assessment
Build a timed implementation rhythm from prompt to edge cases. Problems are ranked by repeated public catalog sightings.
7 DoorDash-tagged Online Assessment problems available.
| Company | Problem | Difficulty | Public evidence | Action |
|---|---|---|---|---|
DODoorDash | Dasher Pay with Store Waits and Peak HoursHash TableSimulation | Medium | 4 public reportsLast reported Sep 2026 | Practice |
DODoorDash | Closest DashMartMatrixBreadth-First Search | Medium | 2 public reportsLast reported Jul 2026 | Practice |
DODoorDash | Adjust Prices 🍱ArraySegment Tree | Medium | 1 public reportLast reported Oct 2024 | Practice |
DODoorDash | Discount EventsArraySegment Tree | Medium | 1 public reportLast reported Oct 2024 | Practice |
DODoorDash | Team FormationArrayHeap | Medium | 1 public reportLast reported Oct 2024 | Practice |
DODoorDash | Calculate Difference Value 🍧StringTwo Pointers | Medium | 1 public reportLast reported Mar 2024 | Practice |
DODoorDash | Get Sizes of Friends Groups 🥗Union Find | Easy | 1 public reportLast reported Mar 2024 | Practice |
Phone practice path
Phone Screen
Practice solving while explaining assumptions, tradeoffs, and complexity. Problems are ranked by repeated public catalog sightings.
| Company | Problem | Difficulty | Public evidence | Action |
|---|---|---|---|---|
DODoorDash | Dasher Pay with Store Waits and Peak HoursHash TableSimulation | Medium | 4 public reportsLast reported Sep 2026 | Practice |
DODoorDash | Customer Bootstrap APIDesignSimulation | Medium | 2 public reportsLast reported Aug 2026 | Practice |
DODoorDash | Closest DashMartMatrixBreadth-First Search | Medium | 2 public reportsLast reported Jul 2026 | Practice |
DODoorDash | Merchant Capacity Interval MergeArrayHash Table | Medium | 1 public reportLast reported Aug 2026 | Practice |
DODoorDash | Open Restaurants in a City RangeArrayGeometry | Easy | 1 public reportLast reported Aug 2026 | Practice |
DODoorDash | Maximize Total Profit by Assigning Chefs to DishesGreedySorting | Medium | 1 public reportLast reported May 2026 | Practice |
DODoorDash | Return Priority of Order IDsArrayHeap | Medium | 1 public reportLast reported Jun 2025 | Practice |
Onsite practice path
Onsite
Practice complete solutions and defend the choices behind them. Problems are ranked by repeated public catalog sightings.
| Company | Problem | Difficulty | Public evidence | Action |
|---|---|---|---|---|
DODoorDash | Random Dasher Set OperationsArrayHash Table | Medium | 3 public reportsLast reported Sep 2026 | Practice |
DODoorDash | Customer Bootstrap APIDesignSimulation | Medium | 2 public reportsLast reported Aug 2026 | Practice |
DODoorDash | First Unique ID in a StreamHash TableQueue | Medium | 1 public reportLast reported Aug 2026 | Practice |
DODoorDash | Minimum Parenthesis Removals and Their IndicesStringStack | Easy | 1 public reportLast reported Aug 2026 | Practice |
DODoorDash | Minimum Processing Speed with Multiple RidersArrayBinary Search | Hard | 1 public reportLast reported Aug 2026 | Practice |
DODoorDash | Minimum Single-Rider Processing SpeedArrayBinary Search | Medium | 1 public reportLast reported Aug 2026 | 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.
- 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.
- 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.
- 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 reported Aug 2026
Design a Scheduled Job Execution System
Design a durable service that stores future jobs, dispatches them when due, and records retryable execution outcomes safely.
Open practiceSystem designLast reported Aug 2026
Design a Sliding-Window Restaurant Leaderboard
Design a seconds-fresh top-ten restaurant leaderboard over a sliding one-hour order window.
Open practiceProject codingLast reported Aug 2026
Build a Refund DAG with Local HTTP Services
Implement a refund workflow DAG with distinct local HTTP services, partial refunds, and a way to keep users from waiting on slow workflow execution.
Open practiceProject codingLast reported Aug 2026
Debug Two Routing Strategies
Repair broken round-robin and consistent-hash routing implementations and verify the result.
Open practiceProject codingLast reported Aug 2026
Integrate Three Profile Services
Complete an aggregate service that combines user, payment, and address data from three provided service templates.
Open practiceSystem designLast reported 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 practiceSystem designLast reported 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 practice03 · 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 3 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