Data Engineering Graduate

This backend-focused role involves building and maintaining scalable ETL/ELT data pipelines and automated data assets using Python, SQL, and Spark to support Visa’s global analytical and product development teams.

About Us
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. Progress starts with you.

Job Description

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

As part of your graduate rotation, you will:

• 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

Basic 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.