Doordash Phone Screen and Virtual Onsite Interview 2025
Summary
I recently went through the phone screen and virtual onsite interview process at Doordash for a position in 2025. The interviews covered a range of topics including data structures and algorithms, system design, coding craft, debugging, and behavioral questions.
Full Experience
I had my interview experience with Doordash, encompassing both a phone screen and a virtual onsite for a 2025 role.
During the Phone Screen, I encountered a question that required me to build an adjacency map for a given tree structure. Following that, I had to determine the time it would take to 'flood' the entire tree, which was an interesting graph traversal problem.
The Virtual Onsite was quite comprehensive, broken down into several distinct rounds:
- Code Craft: This session involved a coding question centered around dasher pay. I was tasked with structuring the code to effectively solve the problem and then demonstrate its execution.
- Debugging: I was presented with a scenario involving a broken round robin network router. My challenge was to identify and fix the issues to ensure all the test cases ran successfully.
- System Design and Domain Knowledge: This combined session had two parts. For Domain Knowledge (DK), I discussed a significant project I had worked on previously. In the System Design (SD) portion, I was asked to design a food review application from scratch.
- Hiring Manager Chat: This was a discussion-based round where I answered questions about my past professional experiences and the key deliverables I was responsible for in previous roles.
Interview Questions (2)
Given a tree, the task is to first construct its adjacency map. Subsequently, determine the minimum time required to 'flood' or propagate information across the entire tree, implying a traversal mechanism where nodes are processed sequentially or in waves.
Design a scalable and robust food review application. This typically involves considering aspects such as user authentication, submitting and viewing reviews, rating systems, searching for restaurants, data storage (reviews, restaurants, users), image uploads, and potential features like social sharing or recommendation engines.