Uber Interview Questions — Page 33

Uber·Software Engineer·Technical Phone Screen

May 2026

Uber SWE interview with a data structure design problem around customer revenue and referral tracking. Pretty involved for a coding round, felt more like a mini system design embedded in a DSA question.

Design a data structure that tracks customer revenue and referral credit. It needs to support inserting new customers (with or without a referrer), where inserting with a referrer also bumps the referrer's total revenue. There's also a query that returns up to K customer IDs whose total revenue meets a minimum threshold, ordered by smallest revenue first.

“The insert operations are straightforward enough but the getLowestK query is where things get interesting.”

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Uber·Software Engineer·Technical Phone Screen

May 2026

Uber SWE coding round, pretty standard algorithmic problem but the follow-up questions are where things got interesting. Worth knowing your complexity analysis cold before going in.

Given an array of strings, group all anagrams together and return the groups.
What is the time and space complexity of your approach, and how do you justify it?
How would you adapt this solution if the input was too large to fit in memory, such as billions of strings being streamed from disk? What becomes the bottleneck when strings are very long?

“The core problem wasn't hard.”

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Uber·Frontend Engineer·Technical Phone Screen

May 2026

Uber frontend interview that threw a classic graph problem at me, which I was not expecting for a frontend role. Pretty standard technical phone screen vibe.

Given a list of flights with source, destination, and cost, find the cheapest route between two cities using at most k stops. Return -1 if no route exists.

“Wasn't ready for a graph question in a frontend screen, so I froze for a bit.”

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Uber·Software Engineer·Technical Phone Screen

May 2026

Uber SWE interview, system design flavored coding round. One problem, a meeting room scheduler, with a follow-up on data structure choice. Pretty focused session, no behavioral stuff at all.

Design a meeting scheduler: given a list of rooms, each with existing meetings as [start, end] intervals, implement a function that takes a new meeting [s, e] and returns any room ID that can fit it without overlap, or null if none can.

“My first instinct was to sort and binary search within each room's meeting list to find the insertion point, then just check the neighbors for overlap.”

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Uber·Product Manager·Onsite - Product Sense / Strategy

May 2026

Interviewed for a PM role at Uber and got hit with a question about COVID's impact on the business. Pretty focused session, not a lot of fluff.

How did COVID-19 impact Uber's business, and how should the company respond?

“This felt like a trap disguised as a simple current-events question but I caught myself before just listing obvious stuff like 'rides dropped.' I tried to break it into the two sides of the marketplace, drivers and riders, and then talk about how Eats actually became a lifeline.”

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Uber·Data Scientist·Take-home Assignment

May 2026

Uber data science take-home that looked straightforward on paper until you actually had to wire all the pandas steps together in the right order. Six tasks, two CSVs, a lot of edge cases baked in quietly.

Load two CSV files into DataFrames and verify the ingest by displaying the first two rows and last row of the trips data.
Drop rows with missing fare values or missing/empty route strings, and make sure the fare column is actually numeric after cleaning.
Split the route column on the pipe character into separate origin and destination columns, trim whitespace from both, and drop rows where the split produces fewer than two parts.
Merge the cleaned trips data with the drivers data on driver ID using a left join, then filter to keep only rows that matched a driver record.
Build a per-driver summary showing trip count, average fare rounded to two decimals, and the average fare across each driver's last three trips ordered by timestamp. If a driver has fewer than three trips, average over however many they have.
Return the top two drivers ranked by average fare descending, with ties broken by trip count descending and then driver name ascending. Also print the final DataFrame's column types.

“Basically a sanity check step, nothing tricky.”

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Uber·Frontend Engineer·Onsite - System Design / Architecture

May 2026

System design round at Uber for a frontend engineer role, centered entirely on designing an online calendar service like Google Calendar. Heavy emphasis on the client-side architecture, not just backend services. A lot to cover and the recurrence model alone could eat your whole session if you're not careful.

Design an online calendar service (like Google Calendar) that supports individual and shared calendars, with event CRUD across day/week/month/agenda views, attendee invites, recurring events with exceptions, time zones, reminders, conflict detection, and free/busy checks. Weight the design toward the frontend client experience.
How would you implement 'edit this and all following events' on a recurring series at the data model level, and what does it cost in extra rows or rule splits?
A shared team calendar has 50,000 events visible in a single month and the month view is janky. How do you diagnose and fix both the frontend rendering and the data fetch path?
How do you efficiently compute free/busy availability across 20 attendees for a 30-minute meeting slot, and what do you precompute versus compute on demand?
A user in New York creates a weekly 9am recurring event, then moves to Tokyo. What happens to past and future instances, and what's the correct product behavior?

“This is the whole question, basically.”

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Uber·Software Engineer·Onsite - Behavioral / Leadership

May 2026

Behavioral round for an EM role at Uber. One question, but it was a meaty one and they clearly wanted a real story, not a framework recitation.

Walk me through how you handled a low performer on your team: how you spotted the issue, what feedback you gave, what the improvement plan looked like, how you supported them, and what happened in the end.

“This is the question I always feel semi-prepared for and then fumble in the details.”

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Uber·Data Scientist·Technical Phone Screen

May 2026

Uber data scientist interview with a pandas/stats coding question that looked straightforward on the surface but had a few moving parts. The DiD component was the real test, the type conversion and imputation were just setup.

You have a pandas DataFrame with columns for unit ID, group (treatment or control), period (pre or post), and an outcome variable stored as strings with exactly one missing value. Convert the outcome to integer, impute the missing value using the unconditional mean of non-missing values, then compute a difference-in-differences estimate of the treatment effect.

“The string-to-int conversion and mean imputation parts I got through fine.”

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Uber·Software Engineer·Recruiter / HR Screen

May 2026

Prepped for a Senior Program Manager screen at Uber and worked through the standard behavioral set you'd expect for a cross-functional PM role. Nothing too surprising, but the data question had more depth to it than I anticipated.

Why do you want to work at Uber specifically?
What makes you a strong fit for this program management role?
Where do you see your career in the next 3 to 5 years?
Walk me through the project you are most proud of.
Describe a time you used data or metrics to change a decision or shift how a project was executed.

“I rambled a bit here.”

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