At a Glance
- Tasks: Build scalable data pipelines and automate processes to support Visa's analytical work.
- Company: Join Visa, a global leader in payments technology with a mission to uplift everyone.
- Benefits: Gain valuable experience, work with cutting-edge tech, and enjoy a collaborative environment.
- Other info: Dynamic role with opportunities for growth and collaboration across global teams.
- Why this job: Make a real impact on data systems that power financial transactions worldwide.
- Qualifications: Graduating in 2025 or 2026 with a technical degree and strong coding skills.
The predicted salary is between 28000 - 38000 £ per year.
Visa is a world leader in payments technology, facilitating transactions between consumers, merchants, financial institutions and government entities across more than 200 countries and territories, dedicated to uplifting everyone, everywhere by being the best way to pay and be paid. At Visa, you'll have the opportunity to create impact at scale — tackling meaningful challenges, growing your skills and seeing your contributions impact lives around the world. Join Visa and do work that matters – to you, to your community, and to the world.
As a Data Engineering Graduate, you will play a key role in building the scalable data foundation that powers Visa’s analytical, data science, and product development work across Europe. Unlike traditional Data Science roles focused on modelling or insight generation, Data Engineering focuses on developing data pipelines, transforming large datasets, automating processes, and enabling teams to operate efficiently and at scale.
You’ll work closely with Data Engineers and Data Scientists to build repeatable, reusable, and automated data assets that support client projects across Europe. Much of the work is backend-focused, requiring strong coding foundations and an engineering-first mindset. While the role is not typically client-facing, strong communication is required to work effectively in a global team environment.
What You’ll Do
- Develop a deep understanding of Visa’s data ecosystem and how data is used across Data Science, Product, and Analytics teams.
- Build, test, and maintain ETL/ELT data pipelines using Python, SQL, Spark, and other big-data tools.
- Support the design and delivery of scalable, reusable data assets to be used repeatedly across client engagements.
- Automate and standardize backend data workflows to improve the reliability and consistency of data used by downstream teams.
- Work with large datasets, performing transformations and ensuring data quality, integrity, and accuracy.
- Collaborate with global Data Engineering teams (North America & other regions) on productionizing and maintaining key data assets.
- Participate in code reviews, contribute to technical documentation, and follow engineering best practices including Git-based version control and CI/CD.
- Troubleshoot data pipeline issues and assist with performance optimization.
Qualifications
- Permanent right to work in the UK. Please specify this on your CV.
- Graduating in 2025 or summer 2026 with a Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, Mathematics, Engineering, or another technical field - ready to start the role in September 2026.
- Strong programming foundations in Python and SQL.
- Interest in backend engineering, data systems, and scalable data processing.
- Familiarity with at least one big-data or distributed computing framework (e.g., Spark, Hadoop, Hive).
- Strong analytical thinking and problem-solving skills.
- Ability to communicate clearly in English, both written and verbal.
Preferred Qualifications
- Experience or exposure to:
- Data pipeline development (ETL/ELT)
- Git or other version control systems
- Workflow orchestration tools (Airflow, Luigi, Prefect)
- Cloud platforms (AWS, GCP, Azure)
- Unix/Linux command line
- Interest in scaling data engineering processes and learning software engineering best practices.
- Ability to collaborate effectively with teammates across geographies.
Visa is an EEO Employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status. Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with EEOC guidelines and applicable local law.
Data Engineering Graduate in London employer: Visa
Visa is an exceptional employer that fosters a dynamic work culture, encouraging innovation and collaboration among its employees. With a strong focus on professional development, Visa offers numerous growth opportunities and the chance to work on cutting-edge financial technologies in a global environment. Located in a vibrant area, employees benefit from a supportive atmosphere that values diversity and inclusion, making it a rewarding place to build a meaningful career.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineering Graduate in London
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Visa!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Data Engineering Graduate at Visa.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Visa.
✨Apply Directly through Our Website
When you find a suitable opening like Data Engineering Graduate at Visa, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Data Engineering Graduate in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Visa, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Visa. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Visa
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Visa!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.