DoorDash Interview Questions — Page 40

DoorDash·Software Engineer·Technical Phone Screen

Jul 2026

DoorDash coding screen with a custom array simulation problem. The problem looked like a heap question at first glance but had enough edge cases to slow me down.

Given an array of distinct positive integers, repeatedly find all 'eligible' elements (those greater than their current neighbors, with boundary elements only needing to beat their single neighbor), pick the smallest eligible element, remove it, and continue until the array is empty. Return the order in which elements were removed.

“My first instinct was to reach for a heap and call it done.”

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DoorDash·Software Engineer·Onsite - System Design / Architecture

Jul 2026

DoorDash system design round focused on building a fault-tolerant bootstrap API that fans out to multiple downstream services. The question had a lot of moving parts and the discussion kept expanding into territory I wasn't fully prepared for.

Design a bootstrap API that calls three downstream services in sequence, builds a composite response from their outputs, and gracefully handles failures at either the call or parse stage without aborting the entire request.
How would you extend this pattern to support timeouts, retries, and parallelism for independent service calls?

“I started with a straightforward sequential loop and null-on-failure logic, which felt right but maybe too simple for the level they expected.”

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DoorDash·Data Scientist·Technical Phone Screen

Jul 2026

DoorDash data science case focused entirely on a marketplace expansion problem: should bike dashers be allowed in a city currently dominated by cars and scooters. It was a deep, multi-part question that touched on everything from experiment design to network effects, and I left feeling like I'd only scratched the surface on a few of the sub-parts.

What historical marketplace data would you look at to determine whether a city or specific zones within it are good candidates for bike dashers?
What primary, secondary, and guardrail metrics would you track across consumer, merchant, dasher, and unit economics dimensions when evaluating bike dashers?
How would you design an A/B test or marketplace experiment to measure the causal impact of enabling bike dashers in a city?
Bike dashers affect dispatch and matching for all orders in a zone, not just their own. How do you account for these spillover effects in your experiment design and analysis?
What experimental outcomes would lead you to fully launch, partially roll out, or pull back the bike dasher program?

“This part felt manageable.”

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DoorDash·Software Engineer·Onsite - System Design / Architecture

Jul 2026

DoorDash system design round where they wanted a full real-time metrics monitoring platform from scratch. Pretty intense scope for a single session, covering ingest all the way through alerting and retention policy.

Design a real-time monitoring system that ingests metrics from many services, supports user-defined alerts, and lets users query and visualize time-series data on dashboards.

“This one sprawled fast.”

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DoorDash·Software Engineer·Onsite - System Design / Architecture

Jul 2026

DoorDash system design round focused entirely on a gnarly incident scenario involving a payment-integration service. One long, multi-part question that kept branching into follow-ups. Pretty intense for what felt like a single prompt.

Your internal payment-integration service is showing high CPU and memory usage, autoscaling nodes keep crashing on startup, upstream traffic is 10x normal, and downstream calls to a financial institution are timing out with no error details. No recent deployments. Walk through how you'd mitigate the incident immediately, investigate root cause systematically, and prevent recurrence long-term.

“This question is basically three questions stitched together and they absolutely expect you to cover all three.”

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DoorDash·Machine Learning Engineer·Technical Phone Screen

Jul 2026

DoorDash ML engineer screen, just one coding problem the whole time. Pretty straightforward BST question but the floating-point angle tripped me up for a second.

Given a binary search tree and a floating-point target value, find the node value in the tree that is closest to the target. If two values are equally close, return the smaller one.

“The BST traversal part was fine, I've done that before.”

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DoorDash·Software Engineer·Technical Phone Screen

Jul 2026

Analytics Engineer case interview at DoorDash focused entirely on the customer support domain. Three meaty open-ended problems back to back, all grounded in the same schema, which was a nice touch but also meant there was nowhere to hide if you didn't know the data model cold.

Design a fair method to allocate salary costs or performance-based compensation across support agents using completed tickets. How would you account for ticket difficulty, cases where multiple agents touched the same ticket, quality signals, and the risk of agents gaming the system?
A core support KPI drops suddenly. Walk through how you'd figure out whether the cause is a tracking or instrumentation change, normal seasonality, a shift in the mix of ticket types coming in, a staffing issue, or an actual operational problem.
Complaint volume is rising due to merchants preparing wrong orders, couriers picking up the wrong bag, or couriers delivering to the wrong customer. What metrics would you track, how would you pinpoint the main driver, and what interventions would you suggest to prevent these errors?

“This is the kind of question where you can go in ten different directions and none of them feel fully right.”

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DoorDash·Software Engineer·Onsite - Behavioral / Leadership

Jul 2026

Behavioral round at DoorDash for a software engineer role. Two questions, both pretty standard conflict and mistake territory, but the follow-ups they hint at can get uncomfortable fast if you haven't actually thought through what changed afterward.

Tell me about a time you had a conflict with a teammate or someone from another team. What was the disagreement, what did you do, and how did it end?
Describe a mistake you made at work. What happened, how did you handle it, and what did you actually do differently going forward?

“I went with a story about a design disagreement with a product partner.”

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DoorDash·Software Engineer·Onsite - System Design / Architecture

Jul 2026

DoorDash system design round focused entirely on building an in-memory path registry, kind of like a mini filesystem. The problem started simple but the follow-ups kept stacking and by the end I was juggling subtree deletion rules and watch callbacks at the same time.

Design an in-memory hierarchical path registry that supports creating a path with an integer value and retrieving a value by path (returning -1 if the path doesn't exist). The root '/' exists implicitly, a path can only be created if its parent exists, and re-creating an existing path should fail.
How would you extend the design to support update and delete operations, including rules around subtree deletion?
How would you add wildcard query support to the path registry, so a query like '/a/*/c' can match multiple paths?
How would you implement watch callbacks that fire when a specific path or any path within a subtree changes?

“I went straight to a trie-backed structure with a hashmap at each node for children.”

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DoorDash·Data Scientist·Technical Phone Screen

Jul 2026

DoorDash data science interview with a meaty experiment design question centered on a new bike delivery feature. The whole session was basically one long case and they pushed hard on every layer of it.

Design an experiment to evaluate whether launching a bike delivery option across a subset of cities is beneficial. Walk through your goal, metrics, randomization strategy, experiment design, potential biases, analysis approach, and how you'd size the test.

“This is a beast of a question.”

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