DoorDash Interview Questions — Page 38

DoorDash·Software Engineer·Onsite - System Design / Architecture

Jul 2026

System design round at DoorDash, one big question that sprawled into basically every hard distributed systems topic at once. Felt like they were stress-testing how far you could go before you started hand-waving.

Design a recurring donation service where users can schedule charges to a charity every 3 days. Cover the API for creating and canceling schedules, the worker that triggers each charge, async payment processor integration, idempotency on the charge path, failure handling, and how users view their donation history. Also discuss data modeling and how the system scales.

“This one kept expanding.”

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DoorDash·Data Scientist·Technical Phone Screen

Jul 2026

DoorDash data science interview focused entirely on marketplace experimentation across three fairly meaty scenarios: auto-applying credits at checkout, duplicate restaurant listings in search, and a restaurant promotions product. No coding, just product analytics and experiment design the whole way through.

How would you design an experiment to test auto-applying customer credits at checkout by default, and what should the primary metric be?
What tradeoffs exist between checkout conversion, credit burn, platform margin, and long-term retention when auto-applying credits?
When the top organic result and the top sponsored result in search are the same restaurant, is showing both listings good or bad for the marketplace?
If you decide to remove duplicate restaurant listings from search results, how would you test that change and what metrics would cover user experience, ad performance, and overall marketplace value?
How would removing a duplicate listing affect lower-ranked restaurants, and how do you account for that in your experiment design?
How would you increase restaurant adoption of the existing fixed-discount promotion feature?
If restaurants can customize their promotion format rather than using a fixed template, how would you design and test that product?
How would you compare the new customizable promotion product against the old fixed-template product, and how do you separate incremental lift from cannibalization or adverse selection?

“This one tripped me up more than I expected.”

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DoorDash·Software Engineer·Onsite - System Design / Architecture

Jul 2026

DoorDash system design round focused entirely on consistent hashing. Pretty deep dive, more theory-heavy than I expected for a SWE role.

Design a consistent hashing system with APIs for adding a node (with weight), removing a node, and looking up which node owns a given key. Use virtual nodes to minimize remapping when the cluster changes.

“This was the whole interview, basically.”

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DoorDash·Machine Learning Engineer·Technical Phone Screen

Jul 2026

DoorDash ML engineer screen with a grid/heatmap coding problem. Pretty algorithmic for an MLE role but the follow-up about optimizing with a 2D difference array is what made it interesting.

Given an n x n grid and a list of restaurants, each defined by a position, a radius, and a delivery count, compute a heatmap showing the expected number of deliveries at each cell. Each restaurant contributes its delivery count to every cell within a (2r+1) x (2r+1) square centered on it, clipped to the grid boundaries.

“The naive approach is obvious, just loop over each restaurant and fill in the square.”

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DoorDash·Software Engineer·Technical Phone Screen

Jul 2026

DoorDash software engineering interview that went deep on string search algorithms. The main problem was KMP-style pattern matching and then they kept pulling the thread with follow-ups for a solid chunk of the session. More theoretical than I expected for a product company.

Implement a function that finds the first occurrence of a pattern string inside a text string, returning the starting index or -1 if not found. Target linear time relative to the combined lengths and space proportional to the pattern.
Compare the naive brute-force approach, KMP, and Rabin-Karp for string matching. Walk through the time and space complexity of each and explain when you'd pick one over another.
How would you handle Unicode text and very large inputs in a string matching implementation? Think about both correctness and memory.
Walk through the important edge cases for string matching: empty pattern, empty text, pattern longer than text, and highly repetitive patterns.
Extend the pattern matcher to support wildcard characters where '?' matches any single character and '*' matches any sequence of zero or more characters. Describe how the semantics work and what the complexity looks like.
Extend the solution to search for multiple patterns simultaneously in a single pass over the text and return all match positions for each pattern. What data structure would you use and how does the runtime compare to running single-pattern search once per pattern?

“I knew this was KMP territory immediately but my failure table construction was shaky under pressure.”

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DoorDash·Software Engineer·Technical Phone Screen

Jul 2026

DoorDash software engineering interview centered on a workflow engine problem for order processing. The coding portion was pretty involved and the follow-ups pushed into design territory fast.

You're given a skeleton workflow engine for order processing where nodes receive an order context and return the next node id. Implement the missing node logic for refunding orders that have timed out, including a timeout decision node, a refund node, and an end node.
How do you ensure the refund workflow is safe to retry and that the same order is never refunded twice?
Write unit tests covering the not-timed-out path, the timed-out refund path, the completed order path, a retry scenario, and a duplicate execution scenario.
How would you extend the workflow to support a partial refund node that refunds either a percentage or a fixed amount?
How would you add a cancel node for timed-out orders where payment has not yet been captured?
When using an AI coding assistant, how do you limit unintended code changes and what does your review process look like before accepting generated code?

“This was a lot more state-management than I expected from what looked like a graph traversal problem.”

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DoorDash·Product Manager·Onsite - Product Sense / Strategy

Jul 2026

PM interview at DoorDash with a product sense question framed around United Airlines. Pretty standard case-style format but the airline context threw me a bit since it's a travel product, not food delivery.

You're a PM at United Airlines. How would you identify and then solve the biggest problem in the post-booking experience?

“I spent the first minute just trying to orient myself because post-booking is a wide surface area.”

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DoorDash·Software Engineer·Onsite - Behavioral / Leadership

Jul 2026

Interviewed for a bizops role at DoorDash, one behavioral question about assertiveness with clients or teammates. Short and to the point, nothing wild.

Describe a situation where you had to push back or be direct with a client or a teammate.

“I had a decent story ready but fumbled the delivery a bit.”

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DoorDash·Software Engineer·Onsite - Behavioral / Leadership

Jul 2026

DoorDash software engineer interview focused entirely on a single deep project walkthrough. They push hard on three specific angles and don't let you stay at a surface level, so if you haven't thought through your own project carefully you'll feel it.

Walk me through a major project on your resume. How large was it, what specifically did you own versus what the team owned, and how did the scope change as the project progressed?
How did you drive the key technical or organizational decisions on that project? Did you mentor anyone or help unblock the team at any point?
How did you collaborate with product, design, data, and other engineering teams on that project? How did you handle situations where priorities or opinions conflicted?

“The scope question sounds easy until they start slicing it up.”

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DoorDash·Software Engineer·Onsite - System Design / Architecture

Jul 2026

DoorDash system design round focused entirely on building a load balancer from scratch. The question had a lot of moving parts and felt more like a mini-project than a single interview question.

Design a load balancer that distributes requests across N backend servers in strict round-robin order, supporting add, remove, and next-server operations in O(1) average time.
How would you handle servers marked as unhealthy in your round-robin implementation without breaking fairness for the remaining healthy servers?
How do you make nextServer and server update operations thread-safe under concurrent access?
Walk through failure scenarios like a server crashing mid-selection, and describe how you'd design a health check system around that.
Write unit tests for your load balancer implementation and analyze the time and space complexity of your design.

“I went straight for a circular linked list and an index pointer.”

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