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Enterprise · Software Engineer Interview Guide

Interview language: English

How to Pass the RELX Software Engineer Interview in 2026

The RELX DNA (TL;DR)

Discussions often center on how candidates derive actionable insights from complex datasets, particularly in scenarios mirroring LexisNexis or Elsevier's information delivery, emphasizing clarity in methodology and the implications of findings for specific user needs.

The RELX 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 RELX interview outcomes, avoid these common traps:

  • Off-by-one errors in loop or range calculations.
  • Not taking clear ownership or blaming others.
  • Not mentioning specific RELX products or business areas.
  • Not handling concurrent activity streams or large volumes of data.

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Test Yourself: Real RELX Questions

Three real prompts pulled from our database.

Type · motivation

RELX operates in the media and information analytics space. What interests you about our specific mission to help professionals advance their work and make breakthroughs?

Type · algorithmic

Given a list of articles, each with a unique ID and a list of tags, write a function to find all articles that share at least K tags with a given target article. Optimize for scenarios where the number of articles and tags per article can be very large.

Type · architecture

Imagine RELX wants to launch a new feature that personalizes the news feed for each user based on their interests and past interactions. Design the backend services required to support this, including how user profiles are managed, how content is scored and ranked, and how the feed is delivered with low latency.

+ many more questions, signals, and worked examples

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RELX Interview Question Bank

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

9 of 16 questions shown

1

Recruiter Screen

1
  1. 1

    Type · motivation

    RELX operates in the media and information analytics space. What interests you about our specific mission to help professionals advance their work and make breakthroughs?
2

Coding Screen

3
  1. 2

    Type · algorithmic

    Given a list of articles, each with a publication date and a list of keywords, write a function to find the top K most relevant articles for a given search query. Relevance is determined by the number of shared keywords and the recency of the article.
  2. 3

    Type · algorithmic

    You are given a stream of user activity logs, where each log entry contains a user ID and the content ID they interacted with. Design a system to detect if any user has viewed more than N distinct content items within a M-minute sliding window. Return the user IDs violating this condition.
  3. + 1 more questions in this round (sign up to unlock)
3

System Design

3
  1. 4

    Type · architecture

    Design a system to recommend related articles to users based on their reading history and the content of the articles they've viewed. Consider scalability for millions of users and a large article corpus.
  2. 5

    Type · architecture

    Design a content ingestion pipeline for a media platform. This pipeline needs to handle various content formats (text, images, videos), extract metadata, perform basic content analysis (e.g., keyword extraction), and store it efficiently for search and retrieval. Discuss potential bottlenecks and how to mitigate them.
  3. + 1 more questions in this round (sign up to unlock)
4

Onsite Coding

4
  1. 6

    Type · algorithmic

    Implement a function that takes a large text document and returns the N most frequent words, ignoring common stop words (like 'the', 'a', 'is'). The function should be efficient for documents potentially gigabytes in size.
  2. 7

    Type · algorithmic

    Given a list of articles, each with a unique ID and a list of tags, write a function to find all articles that share at least K tags with a given target article. Optimize for scenarios where the number of articles and tags per article can be very large.
  3. + 2 more questions in this round (sign up to unlock)
5

Behavioral / Leadership

5
  1. 8

    Type · Conflict Resolution

    Tell me about a time you had a significant disagreement with a colleague or manager. How did you approach the situation, and what was the outcome?
  2. 9

    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, fix, and prevent recurrence?
  3. + 3 more questions in this round (sign up to unlock)

Unlock all 16 RELX 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 RELX

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

Compare RELX with similar employers

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

Practice RELX interviews end-to-end

Sample answers

What a strong answer to these RELX interview questions shows.

RELX operates in the media and information analytics space. What interests you about our specific mission to help professionals advance their work and make breakthroughs?

A strong answer shows: Enthusiasm for RELX's mission; Understanding of RELX's market; Alignment of personal goals with company mission.

Given a list of articles, each with a unique ID and a list of tags, write a function to find all articles that share at least K tags with a given target article. Optimize for scenarios where the number of articles and tags per article can be very large.

A strong answer shows: Use of hash sets for efficient tag comparison; Pre-processing or indexing strategies to speed up queries; Clear logic for counting shared tags; Consideration of time complexity.

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