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DoorDash interview notes, page 32 of 42

Large Enterprises

Most of these DoorDash write-ups come from Software Engineers (265), then Data Scientists (69) and Product Managers (52). The most reported rounds are the technical phone screen (201), the system design round (93), the product sense round (55) and the behavioral / leadership round (36).

416 interview notes · updated Oct 2026

DoorDash·Software Engineer·Technical Phone Screen

Jun 2026
DoorDash coding screen for a software engineer role, one problem the whole time, pretty focused on getting the implementation right and then talking through complexity and edge cases afterward.
  • Given a list of delivery orders each with a start time and end time, calculate total earnings at a fixed per-minute rate, where overlapping active orders multiply the rate for those minutes. You also need to agree on input/output formats with the interviewer, then analyze complexity and write test cases.

“The overlap part is what trips you up if you're not careful.”

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DoorDash·Software Engineer·Onsite - Coding / Algorithms

Jun 2026
DoorDash coding round focused entirely on debugging a pre-written 'Dasher Map' system rather than writing anything from scratch. Three distinct bugs to find and fix, which sounds manageable until you're actually staring at someone else's broken code under time pressure.
  • You're given a buggy 'Dasher Map' system with three known issues: broken randomization, a misconfigured hashmap at initialization, and null pointer errors from faulty key-swapping logic. Find each bug, explain why it's happening, and apply minimal fixes. Add tests where appropriate.

“The randomization bug tripped me up first because I kept looking in the wrong place.”

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DoorDash·Software Engineer·Onsite - System Design / Architecture

Jun 2026
DoorDash system design round focused on a 'bootstrap API' that aggregates multiple downstream services into one composite response. The question had two distinct parts and the optimization half is where things got interesting.
  • You have an API that calls three downstream services in sequence, populating a composite response field by field. If any call or parse fails, that field is null and execution continues. How would you design a test strategy for this system?
  • How would you optimize that same bootstrap API, assuming the three downstream services are independent of each other?

“I went straight to unit tests per service handler with mocked downstreams, which felt solid.”

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DoorDash·Product Manager·Onsite - Product Sense / Strategy

Jun 2026
PM interview at DoorDash with a product sense question framed around the airline industry. Single question, no other details shared about the round or outcome.
  • You're a PM at an airline. Walk me through the worst possible post-booking experience a customer could have.

“This one is deceptively open.”

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DoorDash·Software Engineer·Onsite - System Design / Architecture

Jun 2026
DoorDash system design round focused entirely on building a restaurant review platform. Pretty dense scope for a single session, covering everything from photo storage to ML moderation pipelines.
  • Design a food and restaurant review system. Include the ability to post reviews with ratings, text, and photos; browse and sort reviews with pagination; owner responses; and upvoting reviews for helpfulness.
  • How would you handle high read throughput and abuse resistance for a review platform at scale?
  • Walk through a moderation pipeline for user-generated review content, including both rule-based filtering and ML-based approaches.
  • How would you aggregate review ratings and helpfulness signals to feed into restaurant-level rankings?

“This one sprawled fast.”

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DoorDash·Software Engineer·Hiring Manager Screen

Jun 2026
Interviewed for a bizops role at DoorDash and got hit with a classic pressure-test question about driving conversions fast. Short round, one meaty case question, left me second-guessing my prioritization logic the whole way home.
  • You need to hit 1,000 conversions by next week. How do you approach this?

“I jumped straight into channel prioritization which felt right in the moment but I skipped asking what 'conversions' even meant for them.”

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DoorDash·Software Engineer·Technical Phone Screen

Jun 2026
DoorDash coding round with a deceptively clean problem that turns out to be LCS in disguise. The delivery driver framing was clever enough that I almost missed what they were actually asking.
  • Two delivery drivers each have an ordered list of restaurants to pick up from. They share one car and can only stop at restaurants that appear on both lists, and they must visit them in the same relative order as each driver's original list. Find the longest sequence of restaurants they can visit together.

“Took me a minute to see past the story.”

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DoorDash·Software Engineer·Onsite - System Design / Architecture

Jun 2026
DoorDash system design round where the whole thing was basically one long project deep-dive with follow-ups that kept peeling back layers I wasn't fully prepared for.
  • Walk me through one of your projects in depth, including the architecture decisions you made and why.
  • What alternatives did you consider before settling on this design, and why did you rule them out?
  • What trade-offs did you weigh across cost, latency, complexity, and time to ship when making your design choices?
  • Looking back, what would you change about the design or the decisions you made?

“I picked a project I thought I knew cold and still got tripped up.”

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DoorDash·Software Engineer·Technical Phone Screen

Jun 2026
Did a tech screen for a mid-level SWE role at Doordash. The problem was around dasher payouts with an external delivery API integration, and I couldn't get it to a working state in time. Interviewer was fine, not particularly warm, and threw in a follow-up about handling base pay rates across different countries.
  • Design and implement a dasher payout system that integrates with a delivery API to retrieve dasher activity data.
  • How would your payout system handle different base pay rates across different countries?

“Got through the brainstorming part okay but the actual code never reached a runnable state.”

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DoorDash·Software Engineer·Onsite - System Design / Architecture

Jun 2026
DoorDash system design round for a software engineering role, centered entirely on building a real-time driver pay computation system from scratch. It started as a coding problem and kept expanding into distributed systems territory, which I wasn't fully prepared for.
  • Given a driver's work intervals for a day and a set of peak-hour windows with pay multipliers, compute the driver's total daily pay. Work intervals can cross peak boundaries, so you need to split and pay each sub-interval at the correct rate.
  • How would you design the end-to-end streaming pipeline that continuously computes each driver's daily pay from a high-volume stream of order events?
  • The system receives events with at-least-once delivery guarantees, meaning duplicates, out-of-order arrivals, and late events are all possible. How do you keep daily pay totals correct under these conditions?
  • A day's worth of raw events across all drivers won't fit in memory on one machine. How do you keep streaming state bounded, and how do you recompute historical totals when you need to backfill or reconcile?
  • If a consumer crashes mid-day, how do you recover without losing any pay or double-counting it?
  • If your processing pipeline needs to call an upstream service per event, how do you protect both your system and theirs under high load?
  • Peak window configurations for today are updated at 5pm, changing a multiplier for a window that already passed. How do you fix the already-accumulated pay for affected drivers, and what does the driver-facing number show in the meantime?
  • A bug shipped this morning that over-counted peak pay for some drivers. Walk through how you'd detect it, recompute correct totals from the raw event log, and reconcile without anyone getting paid twice.
  • The driver app needs to show each driver their pay so far today with sub-second latency, at scale across millions of drivers. How does the read path differ from the write path?
  • One driver or order key is generating way more events than others, causing one consumer partition to lag badly. How do you detect and fix the skew without breaking per-key ordering?

“This looked like a clean interval math problem and I dove straight into slicing each interval at every peak boundary.”

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