Walmart software engineer candidates report recruiter or HR screens, Karat or live data-structure coding, system design and behavioral manager rounds, though one loop had no live coding. Formats vary by team.
$148K
Avg. Base Comp
$230K
Avg. Total Comp
Not reported
Typical Rounds
Not reported
Process Length
Walmart's software engineer interviews do not follow one fixed script. Candidates describe very different loops. At one end is a conversational process: an HR screen, then informal conversations with hiring managers and team members, with no live coding. At the other end are multi-stage processes with a recruiter screen, a Karat technical screen, coding rounds, system design and a hiring manager interview.
Coding questions center on data structures. Candidates report these problems:
One Karat candidate faced a treasure-room logic problem with vague instructions in a stripped-down editor, so restating requirements before coding is worth the time. Another described an object-oriented design assessment where the code was not compiled or tested. Its questions resembled real internal systems and emphasized tradeoffs.
Core Java and current project experience come up in some loops, while others probe React Native or the backend languages you know. Check the team's stack before you prepare.
Design and behavioral rounds round out most processes. Candidates report system design challenges and manager conversations about the architecture of systems they built before. Behavioral questions cover past projects, conflict, difficult situations and teamwork, so prepare concrete examples with clear context, actions and results.
Synthesized from 49 candidate reports by our editorial team.
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| Question | |
|---|---|
| Empty Neighborhoods | |
| Subscription Overlap | |
| Customer Orders | |
| Top 3 Users | |
| Over 100 Dollars | |
| Scrambled Tickets | |
| Bagging vs Boosting | |
| Last Transaction | |
| P-value to a Layman | |
| Triplet Counting | |
| Groups of Anagrams | |
| Longest Increasing Subsequence | |
| Cumulative Sales Since Last Restocking | |
| Valid Anagram | |
| Hurdles In Data Projects | |
| Order Addresses | |
| Highest Average | |
| Rider Discount | |
| Black Friday Shopping Spree | |
| Seasonal Product Performance Analysis | |
| Type I and II Errors | |
| Check Matching Parentheses | |
| Moving Window | |
| Employee Benefits Outreach | |
| Deciding Between Solutions | |
| Scalable Data Pipelines | |
| Testing Constraints | |
| Marketing Workflow Optimization | |
| Client Solution Pushback |
Synthesized from candidate reports. Individual experiences may vary.
Candidates report an initial recruiter or HR call covering background and fit. For an intern candidate, it included college projects, coursework, career goals and how team matching works.
Some candidates report a third-party Karat interview with a coding problem. One example was a treasure-room logic prompt with vague instructions. The environment lacked IntelliSense or AI help, so restate requirements before coding.
Technical rounds typically combine data structures with discussion of project work. Candidates report a custom HashMap with collision handling, an anagram check, a BST in Python, binary search and a streaming largest-value problem. One candidate described a process with no live coding.
Some candidates report a system design challenge. One described an object-oriented design assessment where the code was not compiled or tested. Questions may resemble real internal systems, so be ready to analyze tradeoffs.
Candidates report manager or team-fit conversations on past projects, the architecture of previous systems, conflict and difficult situations. One candidate was asked about React Native experience. Prepare concrete examples with context, actions and results.
