Relx Data Engineer Interview Questions + Guide in 2025

Relx is a global provider of information-based analytics and decision tools for professional and business customers, serving customers in over 150 countries.

As a Data Engineer at Relx, you will play a crucial role in designing, developing, and maintaining scalable data pipelines and infrastructure to support advanced analytics and data-driven decision-making across various product lines. Your key responsibilities will include interfacing with cross-functional teams to gather and translate product requirements into effective data management designs, ensuring efficient data flow and storage, and producing high-quality, defect-free code that adheres to best practices. A successful Data Engineer at Relx will demonstrate proficiency in programming languages such as SQL and Java, possess excellent problem-solving and communication skills, and have a deep understanding of software development methodologies. Your ability to identify opportunities for process improvement and your commitment to ensuring data quality will be vital to your success in this role.

This guide will help you prepare for the interview process by providing insights into the expectations and skills required for the Data Engineer role at Relx, enabling you to present yourself as a strong candidate.

The interview process for a Data Engineer at Relx is structured to assess both technical skills and cultural fit within the team. It typically consists of several stages, each designed to evaluate different aspects of a candidate's qualifications and compatibility with the company's values.

1. Application Submission

The process begins with submitting an application through the company's online portal, often via Workday. Candidates are encouraged to provide a comprehensive overview of their skills, experiences, and motivations for applying to Relx.

2. Initial Phone Screen

Following the application, candidates usually undergo an initial phone screen with a recruiter. This conversation is generally informal and focuses on the candidate's background, interest in the role, and understanding of Relx's products and services. Recruiters may also discuss the candidate's future aspirations within the company.

3. Technical Assessment

Candidates who pass the initial screen may be required to complete a technical assessment. This could involve coding exercises or problem-solving tasks that test proficiency in relevant programming languages such as SQL, Java, or Python. The assessment is designed to evaluate the candidate's technical skills and ability to write efficient, maintainable code.

4. One-on-One Interviews

Successful candidates typically move on to one-on-one interviews with the hiring manager and other team members. These interviews delve deeper into the candidate's technical expertise, including their experience with data pipelines, database management, and data manipulation languages. Interviewers may also explore the candidate's problem-solving abilities and how they approach data engineering challenges.

5. Panel Interview

In some cases, candidates may participate in a panel interview, where multiple interviewers assess the candidate simultaneously. This format allows for a broader evaluation of the candidate's skills and how they interact with various team members. Questions may cover a range of topics, including technical knowledge, teamwork, and communication skills.

6. Final Interview

The final stage often involves a discussion with senior management or stakeholders. This interview may focus on the candidate's alignment with Relx's values, their understanding of the company's mission, and how they can contribute to the team's goals. Candidates may also be asked about their long-term career aspirations and how they see themselves growing within the company.

Throughout the process, candidates are encouraged to ask questions and engage in discussions about the role and the company culture.

As you prepare for your interview, consider the types of questions that may arise during these stages.

Here are some tips to help you excel in your interview.

Understand the Interview Process

The interview process at Relx typically involves multiple stages, including an initial phone screen followed by in-person interviews with the hiring manager and team members. Familiarize yourself with this structure and prepare accordingly. Be ready to discuss your previous experiences and how they relate to the role, as well as your understanding of the company's products and potential areas for improvement.

Showcase Your Technical Skills

As a Data Engineer, proficiency in SQL and familiarity with algorithms are crucial. Brush up on your SQL skills, focusing on complex queries, data manipulation, and optimization techniques. Additionally, be prepared to discuss algorithms and their applications in data processing. While coding exercises may not be a primary focus, demonstrating your technical knowledge through discussions will be beneficial.

Communicate Effectively

Relx values strong communication skills, so be prepared to articulate your thoughts clearly and concisely. During the interview, take the time to explain your thought process when answering questions. This not only showcases your technical expertise but also your ability to collaborate with cross-functional teams. Practice discussing your past projects and how you communicated with stakeholders to achieve successful outcomes.

Emphasize Problem-Solving Abilities

Expect questions that assess your problem-solving skills, particularly in data management and engineering contexts. Be ready to discuss specific challenges you've faced in previous roles and how you approached them. Highlight your analytical thinking and ability to identify root causes of issues, as well as any automation or efficiency improvements you've implemented in your work.

Align with Company Culture

Relx promotes a healthy work/life balance and values diversity and inclusion. During your interview, express your alignment with these values. Share examples of how you've contributed to a positive team environment or supported diversity initiatives in your previous roles. This will demonstrate that you not only possess the technical skills required but also fit well within the company's culture.

Prepare for Behavioral Questions

While technical skills are essential, behavioral questions will also play a significant role in the interview. Prepare for questions that explore your past experiences, teamwork, and conflict resolution. Use the STAR (Situation, Task, Action, Result) method to structure your responses, ensuring you provide clear and relevant examples that highlight your capabilities.

Follow Up Thoughtfully

After the interview, consider sending a follow-up email to express your gratitude for the opportunity and reiterate your interest in the role. This is also a chance to briefly mention any points you may not have fully addressed during the interview. A thoughtful follow-up can leave a positive impression and reinforce your enthusiasm for the position.

By focusing on these areas, you can present yourself as a well-rounded candidate who is not only technically proficient but also a great fit for the Relx team. Good luck!

In this section, we’ll review the various interview questions that might be asked during a Data Engineer interview at Relx. The interview process will likely focus on your technical skills, problem-solving abilities, and understanding of data management concepts. Be prepared to discuss your experience with data pipelines, database management, and coding practices, as well as your approach to collaboration and communication within a team.

Technical Skills

1. Can you explain the difference between a data mart and a data lake?

Understanding the distinctions between these two data storage solutions is crucial for a data engineer.

How to Answer

Discuss the purpose of each storage type, emphasizing how data marts are structured for specific business needs while data lakes store raw data for broader analysis.

Example

“A data mart is a subset of a data warehouse, designed to serve a specific business line or team, providing structured data for analysis. In contrast, a data lake stores vast amounts of raw data in its native format, allowing for more flexible data exploration and analysis across various domains.”

2. Describe your experience with SQL and how you have used it in your previous projects.

SQL is a fundamental skill for data engineers, and your experience with it will be closely examined.

How to Answer

Highlight specific projects where you utilized SQL for data manipulation, querying, or database management, and mention any complex queries you’ve written.

Example

“In my last role, I used SQL extensively to extract and analyze data from our relational databases. I wrote complex queries involving multiple joins and subqueries to generate reports that informed our marketing strategies, which led to a 20% increase in campaign effectiveness.”

3. How do you ensure the quality and integrity of data in your pipelines?

Data quality is paramount in data engineering, and interviewers will want to know your strategies for maintaining it.

How to Answer

Discuss methods you use for data validation, error handling, and monitoring data quality throughout the pipeline.

Example

“I implement data validation checks at various stages of the pipeline to catch errors early. Additionally, I use logging and monitoring tools to track data quality metrics, allowing me to quickly identify and resolve any issues that arise during data processing.”

4. What is your approach to designing scalable data pipelines?

Scalability is a key consideration in data engineering, and your design philosophy will be scrutinized.

How to Answer

Explain your process for designing data pipelines that can handle increasing data volumes and how you incorporate best practices.

Example

“When designing data pipelines, I focus on modular architecture, allowing components to be scaled independently. I also leverage cloud-based solutions for storage and processing, which provide the flexibility to scale resources up or down based on demand.”

5. Can you describe a challenging data engineering problem you faced and how you resolved it?

This question assesses your problem-solving skills and ability to handle real-world challenges.

How to Answer

Provide a specific example of a problem, the steps you took to analyze and resolve it, and the outcome of your efforts.

Example

“I once encountered a significant performance issue with a data pipeline that was causing delays in data availability. I conducted a thorough analysis and discovered that inefficient queries were the bottleneck. By optimizing the queries and implementing indexing strategies, I reduced processing time by 50%, ensuring timely data delivery.”

Collaboration and Communication

1. How do you approach collaboration with cross-functional teams?

Collaboration is essential in data engineering, and your ability to work with others will be evaluated.

How to Answer

Discuss your communication style and how you ensure alignment with stakeholders from different functions.

Example

“I prioritize open communication and regular check-ins with cross-functional teams. I make it a point to understand their data needs and provide updates on our progress, which fosters a collaborative environment and ensures that we are all aligned on project goals.”

2. Describe a time when you had to explain a technical concept to a non-technical audience.

Your ability to communicate complex ideas simply is crucial in a collaborative setting.

How to Answer

Share an example where you successfully conveyed a technical concept to a non-technical audience, focusing on your approach.

Example

“I once had to explain the concept of data normalization to a marketing team. I used analogies related to organizing files in a cabinet, which helped them understand the importance of data structure in improving our reporting accuracy. Their feedback was positive, and they appreciated the clarity.”

3. How do you handle conflicts within a team?

Conflict resolution skills are important for maintaining a productive work environment.

How to Answer

Describe your approach to addressing conflicts, emphasizing communication and collaboration.

Example

“When conflicts arise, I believe in addressing them directly and constructively. I encourage open dialogue to understand different perspectives and work towards a solution that satisfies all parties involved. This approach has helped me maintain strong working relationships within my teams.”

4. What strategies do you use to document your work and ensure knowledge sharing?

Documentation is vital in data engineering for maintaining clarity and continuity.

How to Answer

Discuss your documentation practices and how you facilitate knowledge sharing among team members.

Example

“I maintain comprehensive documentation of data pipelines, including architecture diagrams and code comments. I also conduct regular knowledge-sharing sessions with my team to discuss best practices and lessons learned, ensuring that everyone is on the same page.”

5. How do you prioritize tasks when working on multiple projects?

Time management and prioritization are key skills for a data engineer.

How to Answer

Explain your approach to prioritizing tasks based on project deadlines, impact, and resource availability.

Example

“I use a combination of project management tools and prioritization frameworks to manage my workload. I assess the urgency and impact of each task, allowing me to focus on high-priority items while ensuring that I meet all deadlines effectively.”