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DoorDash interview notes, page 26 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 software engineer coding round, one meaty question about building a checkout price calculator. Felt like a reasonable problem but the edge cases pile up fast and I definitely underestimated the promotion logic at first.
  • Implement a checkout price calculator for a shopping cart that applies at most one promotion from a list, where promotions are either a percentage discount on item subtotal or a fixed-amount discount on the full total including shipping. Return the minimum payable amount and which promotion was chosen.

“I spent way too long on the happy path and almost forgot the clamping to zero requirement until they nudged me.”

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DoorDash·Software Engineer·Technical Phone Screen

Jun 2026
DoorDash coding screen focused on interval merging for a salary calculation problem. Pretty clean problem once you see the sweep-line angle, but I spent too long second-guessing edge cases before the approach clicked.
  • Given a set of possibly overlapping delivery intervals for each courier, compute each courier's total salary where pay is a flat rate per minute of active time. Overlapping intervals for the same courier should be counted only once.

“Took me a minute to realize this was just interval union under a different costume.”

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DoorDash·Software Engineer·Technical Phone Screen

Jun 2026
DoorDash coding round for a software engineer role, one problem focused on building out pay calculation logic for delivery drivers. Pretty domain-specific but not algorithmically brutal.
  • Write a function to calculate a delivery driver's total pay given inputs like base pay, distance traveled, time spent, tips, and any active bonuses or promotions.

“The problem itself isn't hard algorithmically but I spent too long trying to figure out edge cases before writing a single line.”

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DoorDash·Data Scientist·Technical Phone Screen

Jun 2026
DoorDash data science interview with a logistics-focused diagnostic case. The question was framed as a regional manager scenario but was clearly testing structured analytical thinking, not business intuition.
  • Successful deliveries in one territory dropped by 10%. How would you diagnose the root cause? Walk through how you'd slice the data, what hypotheses you'd form, and what statistical tests you'd run.

“This one is deceptively wide.”

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DoorDash·Software Engineer·Technical Phone Screen

Jun 2026
DoorDash coding interview with a grid traversal problem that looks deceptively straightforward until you realize brute force won't cut it.
  • You're given an n x n grid where each cell holds the earliest time you can enter it. Starting at the top-left corner, you can move in four directions but only into a cell when the current time is at least that cell's value. What's the minimum time needed to reach the bottom-right corner?

“My first instinct was BFS and I started coding it before really thinking through the time constraint mechanics.”

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DoorDash·Software Engineer·Technical Phone Screen

Jun 2026
DoorDash software engineering interview with a coding round built around file system design. The base problem is familiar from LeetCode but they extended it pretty significantly, so going in expecting a straightforward solve would've been a mistake.
  • Design a file system that supports Create(path, value), Get(path), Set(path, value), and Delete(path) operations, with appropriate validation on each.

“The base version is manageable if you've seen the LeetCode problem before, but the Set and Delete operations with validation rules added a lot more edge cases than I expected.”

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DoorDash·Software Engineer·Onsite - System Design / Architecture

Jun 2026
DoorDash system design round for a software engineering role. One meaty graph problem that went pretty deep into dynamic connectivity, concurrency, and tradeoffs. Not a casual screen.
  • Design a data structure for an undirected graph of N nodes where each node has an 'alive' flag. Support toggling node status, adding edges only between alive nodes, removing edges, checking if two nodes are in the same connected component among alive nodes, and counting connected components over alive nodes. Discuss time/space complexity, how you'd handle deletions and deactivations (lazy vs fully dynamic), and concurrency if multiple threads call these operations simultaneously.

“This one took me a while to even get my footing.”

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DoorDash·Software Engineer·Hiring Manager Screen

Jun 2026
Interviewed for a BA role at DoorDash, came away thinking it was pretty standard but this one question about communicating to non-technical folks tripped me up more than I expected.
  • How do you present data insights to stakeholders who don't have a technical background?

“I rambled a bit.”

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DoorDash·Software Engineer·Technical Phone Screen

Jun 2026
DoorDash coding round, pretty much one meaty grid problem that kept expanding with follow-ups. The core question was straightforward but the extensions kept coming and I wasn't fully prepared for all of them.
  • Given a 2D grid with warehouses, customers, obstacles, and roads, find the minimum number of steps from any warehouse to each customer cell. Return -1 for unreachable customers. Define your input/output format and justify your data structure choices.
  • How would you scale this solution to handle a grid with millions of cells, considering both memory and time constraints?
  • If road cells have non-uniform movement costs instead of uniform cost-1, how would you adapt your solution?
  • For a subset of customer cells, how would you return the actual paths taken, not just the minimum distances?

“Multi-source BFS was the right move here, seed all warehouse cells at once and let it fan out.”

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DoorDash·Software Engineer·Technical Phone Screen

Jun 2026
DoorDash data science interview with a product analytics case about diagnosing a drop in conversion rates on a food delivery platform. One question, pretty open-ended, felt more like a PM exercise than pure data science but apparently that's the vibe there.
  • Conversion rates on the food delivery app have been dropping for the past week. As the PM, how would you investigate what's causing it?

“I spent way too long trying to be thorough and ended up just listing every possible thing that could go wrong.”

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