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Growth · Software Engineer Interview Guide

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Interview language: English

How to Pass the Carousell Software Engineer Interview in 2026

The Carousell DNA (TL;DR)

Carousell's 'Act like an owner' principle guides the evaluation of candidates, seeking those who demonstrate initiative and impact within their domain. Interviewers grade for resourcefulness in navigating constraints, particularly in scaling the Carousell marketplace or improving user trust with features like CarouPay.

The Carousell Interview Loop

Your onsite loop will typically consist of 5 rounds.

  1. 1

    Round 1

    Recruiter Screen
    Motivation, role fit, logistics.
  2. 2

    Round 2

    Coding Screen
    LeetCode-medium algorithmic problems under time pressure.
  3. 3

    Round 3

    System Design
    Distributed systems, trade-offs at scale, architecture under constraints.
  4. 4

    Round 4

    Onsite Coding
    LeetCode-hard, debugging, code clarity, edge cases.
  5. 5

    Round 5

    Behavioral / Leadership
    Past evidence of ownership, influence, resolving conflict.

The Danger Zone: Top Reasons Candidates Fail

Based on our database of Carousell interview outcomes, avoid these common traps:

  • Not demonstrating a structured approach to learning.
  • Not considering performance implications for a large number of queries.
  • Lack of specific details about the technical aspects of the problem and solution.
  • Lack of consideration for real-time updates vs. batch processing.

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Test Yourself: Real Carousell Questions

Three real prompts pulled from our database.

Type · edge-cases

You are building a feature to calculate shipping costs based on weight, dimensions, and destination. Write a function to handle this calculation, paying close attention to potential edge cases and error conditions.

Type · design

Design a system to detect and prevent fraudulent listings on Carousell. What data points would you use, and what kind of algorithms or rules would you implement?

Type · algorithmic

Given a large dataset of user interactions (views, clicks, purchases) on product pages, design an algorithm to identify 'sessions' of user activity. A session ends after a period of inactivity (e.g., 30 minutes).

+ many more questions, signals, and worked examples

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Carousell Interview Question Bank

A sample from our database, grouped by round. Sign up to see the full set.

9 of 15 questions shown

1

Recruiter Screen

1
  1. 1

    Type · motivation

    What interests you about working at Carousell, specifically within our retail tech domain, and what kind of impact do you hope to make here as a Software Engineer?
2

Coding Screen

3
  1. 2

    Type · algorithmic

    Given a list of product listings, each with a price and a category, write a function to find the top K most frequent categories within a given price range. Assume prices are integers.
  2. 3

    Type · algorithmic

    Design a function that takes a list of user search queries and returns a list of suggested related queries. Consider common misspellings, synonyms, and popular related searches.
  3. + 1 more questions in this round (sign up to unlock)
3

System Design

3
  1. 4

    Type · design

    Design a system to recommend similar products to users based on their browsing history and purchase data on Carousell. Consider scalability for millions of users and products.
  2. 5

    Type · design

    How would you design a real-time notification system for Carousell? Users should receive timely alerts for new messages, offers, and price drops on items they follow. Consider delivery guarantees and fan-out.
  3. + 1 more questions in this round (sign up to unlock)
4

Onsite Coding

4
  1. 6

    Type · algorithmic

    Implement a function to efficiently find the median of a stream of numbers. The numbers arrive one by one, and you need to be able to query the median at any point.
  2. 7

    Type · algorithmic

    Given a large dataset of user interactions (views, clicks, purchases) on product pages, design an algorithm to identify 'sessions' of user activity. A session ends after a period of inactivity (e.g., 30 minutes).
  3. + 2 more questions in this round (sign up to unlock)
5

Behavioral / Leadership

4
  1. 8

    Type · ownership

    Tell me about a time you encountered a significant technical challenge or bug in a production system that was impacting users. What steps did you take to diagnose, resolve, and prevent recurrence?
  2. 9

    Type · collaboration

    Describe a situation where you had a technical disagreement with a colleague or team lead regarding an implementation detail or architectural choice. How did you approach the discussion, and what was the outcome?
  3. + 2 more questions in this round (sign up to unlock)

Unlock all 15 Carousell questions, free

No credit card. Every question with its framework, the grading signals interviewers score against, and a worked answer for each.

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Interview tracks at Carousell

How Carousell's DNA translates across functions. Pick your role.

Compare Carousell with similar employers

Same DNA, different bar. Browse the closest companies in our database and see how their loops differ.

Practice Carousell interviews end-to-end

Sample answers

What a strong answer to these Carousell interview questions shows.

You are building a feature to calculate shipping costs based on weight, dimensions, and destination. Write a function to handle this calculation, paying close attention to potential edge cases and error conditions.

A strong answer shows: Explicit handling of invalid inputs (null, negative, zero, out-of-range).; Clear logic for different shipping tiers or zones.; Consideration of data types and potential precision issues (e.g., floating-point arithmetic).; Robust error handling and informative return values or exceptions..

Design a system to detect and prevent fraudulent listings on Carousell. What data points would you use, and what kind of algorithms or rules would you implement?

A strong answer shows: Identification of relevant data signals (user behavior, listing content, transaction history).; Discussion of both rule-based and ML-based approaches.; Consideration of real-time vs. batch detection.; Strategies for model training, evaluation, and deployment.; Handling of appeals and human review..

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