GeeksforGeeks Experience · Mar 2026 · Bangalore

Walmart SDE III (Backend, 3 YOE) Interview Experience — Bangalore

Data Eng Phone Screen Hard

Interview Experience

I recently went through the Walmart SDE III backend interview process and received an offer.Role: SDE III (Java Backend)YOE: 3 yearsLocation: BangaloreInterviewed On: Octo...

Full Details

I recently went through the Walmart SDE III backend interview process and received an offer. Role: SDE III (Java Backend) YOE: 3 years Location: Bangalore Interviewed On: October, 2025 Applied via: LinkedIn Interview Structure: Total of 3 rounds: DSA LLD + Backend fundamentals Hiring Manager (Behavioral + System discussion) All rounds were done in 3 consecutive days (1 per day) — pretty fast process :)

Round 1 DSA Duration: 1 hrs Difficulty: Medium → Hard level What to expect: Direct or slightly modified versions of problems from LeetCode 150 / NeetCode 150 2 questions to be solved in 1

hr Spiral Matrix problem Linked List (hard-level manipulation problem) My experience: I solved both problems within the allotted time,

passed all test cases, clearly explained my approach, and wrapped up by asking a few questions about the team’s tech stack.

Round 2 LLD + Backend Concepts Duration: 1 hrs 30mins Problem: Design a WhatsApp-like system, with focus on: Chat functionality Search (especially chat search / master search) What the interviewer looked for: 1. LLD Fundamentals Class design Relationships Clean modeling 2. Database Design Schema clarity Trade-offs Indexing (especially for search) 3. API Design Clean endpoints Pagination (this was explicitly expected) Tip: Always mention pagination for search-heavy systems. Bonus discussion: The interviewer went deeper into: Microservices vs Monolith. But interestingly, the focus was more on when NOT to use microservices. Towards the end, I was asked about : Spring Boot annotations Spring Security basics Tip: Using proper terminology (SOLID principles, design patterns, etc.) makes a noticeable difference in LLD rounds

Round 3 Hiring Manager (Offline — Bangalore Office) Duration: 45-50 mins This round was very conversational and comfortable. 1. Project Deep Dive Architecture of past work Leaned towards high-level design Deep dive into: Asynchronous flows Kafka Rule engines (Since my project architecture involved these concepts) 2. Behavioral Questions Conflict resolution Handling escalations Disagreeing with your manager Sample question: Would you push back if code quality is being compromised? 3. Your Questions I asked about: Tech stack Team's work Nature of problems Walmart's work culture Don’t skip this—it leaves a good impression.

Verdict Selected Compensation: 35 LPA (CTC) Final Thoughts: This wasn’t an “out of syllabus” process. It’s quite predictable if you prepare well: Solid DSA Practical LLD Decent backend fundamentals Clear communication No tricks. No surprises. All the best! If you have specific questions, feel free to ask in the comments!

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About This Question

This is a candidate experience report from a walmart interview for a data eng role during the phone screen round reported in 2026.

It covers the following topics: Linked List, Oop, Matrix, Sql, Networking, Stack Queue, System Design, Stack .

Difficulty rating: Hard

About Walmart Interview Reports

This question was reported by a candidate who interviewed at Walmart. 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 Walmart are the higher-signal extractions to take from this report.

For broader preparation context, the Walmart 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 Walmart reports consistently are the ones worth investing in; one-off niche problems are not.

During Your Walmart 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 Walmart 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.