1p3a Experience · May 2026

uber fulltime software engineer tech phone screen: last click attribution system design

SWE Phone Screen newgrad
1 upvote

Interview Experience

光膏组 l5。 一个三姐 貌似是个全新的题 准备了几十道面筋题目一点也没用上 设计一个系统能做last click attribution 有两种event click(timestamp, userId, campaignId) conversion(timestamp, userId) 对于每一次 conversion,需要把它归因到同一个用户最近的一次 click,要求: click 的时间必须早于或等于 conversion 的时间; click 必须发生在固定的 conversion window 内。如果没有符合条件的 click,那么这次 conversion 就是 unattributed。 需要实现的 API: recordClick(userId, campaignId, timestamp) recordConversion(userId, timestamp) getCampaignConversions(campaignId) getUserAttribution(userId) 假设: conversion_window_sec...

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About This Question

This is a candidate experience report from a uber interview for a swe role (newgrad level) during the phone screen round reported in 2026.

It covers the following topics: System Design .

About Uber Interview Reports

This question was reported by a candidate who interviewed at Uber. LeakCode aggregates interview reports from 10+ sources, including 1Point3Acres, Glassdoor, LeetCode Discuss, Blind, Reddit, Indeed, and Nowcoder. Each report is translated where necessary, deduplicated against existing entries, and tagged by company, role, round type, and reporting date.

Use this question as one calibration data point, not a memorization target. Companies typically rotate their question pools every 2-4 months; the exact wording of a 2024 question may differ from what you encounter today. The underlying pattern, difficulty level, and follow-up depth at Uber are the higher-signal extractions to take from this report.

For broader preparation context, the Uber interview process typically includes a recruiter screen, one or two technical phone screens, and a 4-5 round on-site loop covering coding, system design (at L4+ levels), and behavioral. Reports tagged on LeakCode show the round-by-round distribution and typical difficulty calibration. To browse questions filtered by round type and seniority, use the company hub linked above.

How To Practice This Type of Question

Solve similar problems on LeetCode under timed conditions (25-35 minutes per medium difficulty). The goal is pattern recognition: recognize the underlying technique (sliding window, two-pointer, BFS, memoized recursion, etc.) within 60-90 seconds of reading. Strong candidates verbalize their hypothesis out loud before coding, then iterate based on feedback. Weak candidates dive into implementation immediately, lose time on the wrong approach, and run out of time for follow-ups.

Companies update their question pools every 2-4 months. The exact wording of any given question may have been retired by the time you interview. Focus your prep on the pattern, not the specific problem. The patterns that appear in Uber reports consistently are the ones worth investing in; one-off niche problems are not.

During Your Uber Round

Apply the standard interview round template: clarify requirements (2-3 minutes), state your approach out loud and confirm direction with the interviewer (3-5 minutes), code with narration (15-25 minutes), test with concrete examples including edge cases (5 minutes), discuss optimization or trade-offs if time permits (5 minutes). This template is universally accepted across FAANG and adjacent companies; deviating from it produces weaker interviewer feedback signal.

The single most predictive failure mode in Uber reports tagged "no hire": not asking clarifying questions. Interviewers are explicitly trained to weight this. Strong candidates ask 3-5 clarifying questions even on problems that look obvious; weak candidates dive into code immediately. The clarifying-question check is often the first signal recorded in the interviewer's written notes.