DoorDash SDE II Interview Experience: San Francisco Onsite Loop (2021)
Updated July 17, 2026
The candidate interviewed for an SDE II role at DoorDash's San Francisco office in October 2021. The process opened with a remote phone screen built around a single coding question on weighted interval scheduling, then moved into an onsite loop with two coding rounds, a system design round, and a behavioral round.
The first onsite coding round used a DoorDash-flavored delivery-matching problem referenced separately on LeetCode Discuss, while the second worked through an island-counting problem with a follow-up on island area. The system design round asked the candidate to design a donation platform for a large, time-boxed charity campaign built on an existing payment-gateway partnership, and the behavioral round combined values-based questions tied to DoorDash's stated principles with a scenario about reducing delivery inaccuracy. The candidate completed the full loop and was rejected.
How the process went
Phone Screen
A single coding question on weighted interval scheduling, conducted remotely before the onsite loop.
Onsite Coding Round 1
A DoorDash-style delivery-matching problem, titled 'Available Deliveries' and detailed in a separate LeetCode Discuss post.
Onsite Coding Round 2
A grid-traversal problem with a follow-up variant on the same theme.
System Design
Designing a donation platform for a large, multi-day charity event.
Behavioral
Questions tied to DoorDash's stated principles plus an operational scenario on delivery accuracy; the candidate noted these matched a set reported from a separate DoorDash onsite write-up.
Outcome
The candidate completed the full onsite loop and was rejected; the write-up does not say which round the decision hinged on.
Phone Screen
Single technical coding question, conducted remotely
- LeetCode 1235: Maximum Profit in Job Scheduling
Onsite Coding Round 1
A DoorDash-flavored delivery-matching problem
- Available Deliveries — a DoorDash-style scheduling/matching problem, detailed in a separate LeetCode Discuss post.
Onsite Coding Round 2
Grid traversal problem with a follow-up
- LeetCode 200: Number of Islands
- Follow-up: LeetCode 695: Max Area of Island
System Design
Designing a donation platform for a large, time-boxed charity event
- Design a donation app for a 3-day charity event run by DoorDash and its partners across the US, expecting more than 3 million participating customers. The app needed to collect customer name, email, and payment-method details, with DoorDash's existing payment-gateway partnership holding the collected funds and transferring them out later.
Behavioral
Values-based questions tied to DoorDash's stated principles, plus one operational scenario
- Tell me about a time you advocated for someone.
- Tell me about a time you supported an underrepresented group at work.
- Describe a time you failed and what you learned from it.
- Describe a time you received constructive feedback and how you responded.
- Several questions built around DoorDash's stated principles.
- Scenario: how would you reduce inaccurate order deliveries, where inaccuracy covers incorrect or misplaced items, wrong orders delivered to the customer, and an incorrect menu shown in the app?
The candidate noted these behavioral questions matched a set reported from a separate DoorDash onsite write-up.
Key takeaways
- Brush up on interval-scheduling and grid/graph-traversal patterns — weighted job scheduling and island-counting with a follow-up on area both showed up as standalone coding rounds here.
- For DoorDash-flavored design prompts, practice reasoning about data collection and fund flow at scale rather than building a payment system from scratch — this round assumed an existing payment-gateway partnership and asked for the app around it.
- Prepare concrete stories around advocacy, supporting underrepresented colleagues, failure, and feedback — the behavioral round leaned on DoorDash's stated principles rather than generic questions.
- Have a structured answer ready for operational scenario prompts (e.g., reducing delivery inaccuracy) that breaks the problem into its stated sub-causes before proposing fixes.
Practice a DoorDash interview
Rehearse out loud against the kinds of questions in this story — with an AI interviewer that asks follow-ups.
Practice this interviewSource
The questions and process facts come from the candidate's public write-up, linked below. The retelling above is our own summary.
Candidate's public write-up on LeetCode Discuss