Revolut Data Engineer Interview Questions + Guide in 2025

Revolut is a global financial technology company that offers a range of banking services including currency exchange, international money transfers, and cryptocurrency trading.

As a Data Engineer at Revolut, you will play a crucial role in building and maintaining the infrastructure that supports data processing and analytics, facilitating data-driven decision-making across the organization. Your key responsibilities will include designing, constructing, and operating data pipelines, ensuring data quality and integrity, and collaborating with data scientists and analysts to provide them with the necessary data for their analyses. A strong proficiency in SQL and Python, as well as a deep understanding of algorithms, is essential for success in this role. Additionally, you should have experience with various data storage solutions and data modeling techniques, enabling you to optimize data workflows and enhance system performance.

At Revolut, teamwork, innovation, and a strong analytical mindset are highly valued. Being adaptable and capable of working in a fast-paced environment will help you thrive in this role. The insights garnered from this guide will help you prepare effectively for your interview, allowing you to showcase your technical expertise and alignment with Revolut's culture.

The interview process for a Data Engineer role at Revolut is structured and thorough, designed to assess both technical skills and cultural fit. The process typically unfolds in several distinct stages:

1. Initial Screening

The first step involves a brief phone call with a recruiter. This conversation is primarily focused on your background, experience, and motivation for applying to Revolut. Expect general questions about your previous projects and your interest in the role. The recruiter will also provide an overview of the interview process and what to expect in the subsequent stages.

2. Technical Assessment

Following the initial screening, candidates are usually required to complete a technical assessment, often conducted through platforms like HackerRank. This assessment typically includes a mix of SQL and Python coding questions, as well as theoretical questions related to statistics and data analysis. The goal is to evaluate your problem-solving skills and technical proficiency in relevant programming languages.

3. Live Coding Interview

Candidates who pass the technical assessment will move on to a live coding interview. This session involves solving coding challenges in real-time, where you may be asked to implement algorithms or work on data structures. Be prepared to explain your thought process and the decisions you make during the coding exercise, as interviewers will be looking for clarity in your approach and understanding of best practices.

4. Business Case Analysis

After the live coding interview, candidates typically participate in a business case analysis. This stage assesses your ability to apply data engineering concepts to real-world scenarios. You may be asked to design a dashboard, analyze A/B test results, or discuss how you would approach a specific data-related problem. This part of the interview is crucial for demonstrating your analytical skills and understanding of business metrics.

5. Team Fit and Cultural Interview

The final stage usually consists of interviews with team members and possibly a hiring manager. These interviews focus on assessing your fit within the team and the company culture. Expect questions about your previous experiences, how you handle challenges, and your approach to collaboration. This is also an opportunity for you to ask questions about the team dynamics and work environment at Revolut.

6. Final Review

In some cases, there may be a final review stage where senior team members or executives assess your overall fit for the role. This could involve a more in-depth discussion about your career goals and how they align with Revolut's mission and values.

As you prepare for your interview, it's essential to be ready for a variety of questions that will test both your technical skills and your ability to work within a team. Here are some of the interview questions that candidates have encountered during the process.

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

Understand the Interview Structure

The interview process at Revolut typically involves multiple stages, including an initial HR screening, technical assessments, and interviews with hiring managers. Familiarize yourself with this structure so you can prepare accordingly. Expect to encounter coding tasks, theoretical questions, and discussions about your previous projects and their impact. Knowing what to expect will help you manage your time and energy throughout the process.

Prepare for Technical Assessments

Given the emphasis on SQL and algorithms, ensure you are well-versed in these areas. Practice coding challenges on platforms like LeetCode or HackerRank, focusing on SQL queries, data manipulation, and algorithmic problem-solving. Be ready to explain your thought process and the reasoning behind your solutions, as interviewers often look for clarity in your approach.

Showcase Your Projects

During interviews, you will likely be asked about your previous projects and the impact you've made. Prepare to discuss specific examples that highlight your technical skills, problem-solving abilities, and contributions to team success. Use the STAR (Situation, Task, Action, Result) method to structure your responses, making it easier for interviewers to understand your role and achievements.

Emphasize Problem-Solving Skills

Revolut values candidates who can think critically and solve complex problems. Be prepared for scenario-based questions that assess your analytical skills. Practice articulating your thought process when tackling hypothetical situations, and be ready to discuss how you would approach real-world challenges relevant to the role.

Be Ready for Live Coding

Expect live coding sessions where you will need to demonstrate your coding skills in real-time. Familiarize yourself with common coding practices, such as Test-Driven Development (TDD), and be prepared to explain your code as you write it. If you encounter challenges during the session, communicate your thought process clearly, as interviewers appreciate candidates who can articulate their reasoning even when facing difficulties.

Engage with Interviewers

Throughout the interview process, engage with your interviewers by asking insightful questions about the team, projects, and company culture. This not only demonstrates your interest in the role but also helps you assess if Revolut is the right fit for you. Be genuine in your interactions, as cultural fit is an important aspect of the hiring process.

Stay Positive and Resilient

The interview process at Revolut can be lengthy and may involve multiple rounds. Maintain a positive attitude and be resilient, even if you face setbacks. Use any feedback you receive as a learning opportunity to improve your skills and approach for future interviews.

By following these tips and preparing thoroughly, you can enhance your chances of success in the interview process at Revolut. Good luck!

In this section, we’ll review the various interview questions that might be asked during a Data Engineer interview at Revolut. The interview process will likely assess your technical skills, problem-solving abilities, and cultural fit within the company. Be prepared to discuss your previous projects, coding skills, and how you approach data engineering challenges.

Technical Skills

1. Can you explain the differences between SQL and NoSQL databases?

Understanding the strengths and weaknesses of different database types is crucial for a Data Engineer.

How to Answer

Discuss the use cases for each type of database, highlighting their performance, scalability, and data structure differences.

Example

"SQL databases are ideal for structured data and complex queries, while NoSQL databases excel in handling unstructured data and scaling horizontally. For instance, I would use SQL for transactional systems where data integrity is critical, and NoSQL for applications requiring high availability and flexibility, like real-time analytics."

2. How would you optimize a slow SQL query?

Performance optimization is a key responsibility for Data Engineers.

How to Answer

Mention techniques such as indexing, query rewriting, and analyzing execution plans to identify bottlenecks.

Example

"I would start by analyzing the execution plan to identify slow operations. Then, I would consider adding indexes on frequently queried columns and rewriting the query to reduce complexity. For instance, using JOINs efficiently can significantly improve performance."

3. Describe a data pipeline you have built. What challenges did you face?

This question assesses your practical experience in data engineering.

How to Answer

Outline the architecture of the pipeline, the technologies used, and the specific challenges encountered.

Example

"I built a data pipeline using Apache Kafka and Spark to process real-time data from various sources. One challenge was ensuring data consistency across distributed systems, which I addressed by implementing idempotency in data processing."

4. What is your experience with ETL processes?

ETL (Extract, Transform, Load) is a fundamental aspect of data engineering.

How to Answer

Discuss your familiarity with ETL tools and your approach to designing efficient ETL workflows.

Example

"I have extensive experience with ETL processes using tools like Apache NiFi and Talend. I focus on designing workflows that minimize data latency and ensure data quality by implementing validation checks at each stage."

5. Can you explain database isolation levels?

Understanding isolation levels is important for managing concurrent transactions.

How to Answer

Discuss the different isolation levels and their impact on data consistency and performance.

Example

"Database isolation levels, such as Read Uncommitted, Read Committed, Repeatable Read, and Serializable, dictate how transactions interact. For example, Serializable provides the highest level of isolation but can lead to performance bottlenecks due to increased locking."

Problem-Solving and Analytical Skills

1. How would you approach designing a data model for a new application?

This question evaluates your analytical thinking and design skills.

How to Answer

Explain your process for gathering requirements, identifying entities, and defining relationships.

Example

"I would start by gathering requirements from stakeholders to understand the data needs. Then, I would identify key entities and their relationships, using normalization techniques to design an efficient data model that supports the application's functionality."

2. Describe a time when you had to troubleshoot a data issue. What steps did you take?

This question assesses your problem-solving skills in a real-world context.

How to Answer

Outline the steps you took to identify and resolve the issue, emphasizing your analytical approach.

Example

"When I encountered a data discrepancy in our reporting system, I first traced the data lineage to identify where the issue originated. After pinpointing a faulty transformation step in the ETL process, I corrected the logic and implemented additional validation checks to prevent future occurrences."

3. What metrics would you consider when evaluating the performance of a data pipeline?

Understanding performance metrics is essential for continuous improvement.

How to Answer

Discuss key performance indicators (KPIs) relevant to data pipelines, such as throughput, latency, and error rates.

Example

"I would monitor metrics like throughput to assess how much data is processed over time, latency to measure the time taken for data to move through the pipeline, and error rates to identify any failures in data processing."

4. How do you ensure data quality in your projects?

Data quality is critical for reliable analytics and decision-making.

How to Answer

Discuss your strategies for implementing data validation, cleansing, and monitoring.

Example

"I ensure data quality by implementing validation rules during the ETL process, conducting regular audits, and using automated monitoring tools to detect anomalies in real-time. This proactive approach helps maintain high data integrity."

5. Can you describe a situation where you had to work with a cross-functional team?

Collaboration is key in data engineering roles.

How to Answer

Share your experience working with different teams and how you facilitated communication and collaboration.

Example

"I collaborated with product managers and data scientists to develop a new feature that required integrating multiple data sources. I facilitated regular meetings to align on requirements and ensure that the data architecture supported their needs effectively."

Cultural Fit and Motivation

1. Why do you want to work at Revolut?

This question assesses your motivation and alignment with the company's values.

How to Answer

Express your enthusiasm for the company's mission and how your skills align with their goals.

Example

"I admire Revolut's commitment to innovation in the financial sector and its focus on leveraging data to enhance user experiences. I believe my background in data engineering can contribute to building robust data solutions that drive business insights."

2. How do you handle tight deadlines and pressure?

This question evaluates your ability to work in a fast-paced environment.

How to Answer

Discuss your time management strategies and how you prioritize tasks under pressure.

Example

"I thrive under pressure by breaking down tasks into manageable chunks and setting clear priorities. For instance, during a recent project with a tight deadline, I created a detailed timeline and communicated regularly with my team to ensure we stayed on track."

3. What do you consider your biggest achievement in your career so far?

This question allows you to showcase your accomplishments.

How to Answer

Highlight a specific achievement that demonstrates your skills and impact.

Example

"My biggest achievement was leading a project that improved data processing efficiency by 40%. I implemented a new data pipeline architecture that reduced processing time and enabled real-time analytics, significantly enhancing our decision-making capabilities."

4. How do you stay updated with the latest trends in data engineering?

This question assesses your commitment to continuous learning.

How to Answer

Discuss your methods for staying informed about industry trends and technologies.

Example

"I stay updated by following industry blogs, participating in online courses, and attending data engineering meetups. I also engage with the data engineering community on platforms like LinkedIn to share insights and learn from others."

5. What makes you a good fit for our team?

This question evaluates your self-awareness and understanding of team dynamics.

How to Answer

Highlight your skills, experiences, and values that align with the team culture.

Example

"I believe my strong technical skills, collaborative mindset, and passion for data-driven decision-making make me a great fit for your team. I value open communication and am always eager to learn from my colleagues, which I think aligns well with Revolut's culture."