Senior Staff Data Engineer

Visa; Cambridge; Hybrid; GBP 70,000 - 90,000; Full time

Job summary

A leading payments technology company in Cambridge is seeking a Senior Consultant Data Engineer to design and optimize data pipelines for AI model development. The role involves mentoring junior engineers, leading projects, and collaborating with cross-functional teams to ensure robust data solutions. Candidates should have at least 5 years of experience, mastery in Apache Spark, and proficiency in Python. This position offers a hybrid work model.

Qualifications

• 5+ years of experience in software engineering roles.
• Strong experience with distributed computing environments.
• Familiarity with cloud-based big data platforms.

Responsibilities

• Design and build high-performance data pipelines.
• Mentor junior engineers and optimize workflows.
• Collaborate with teams to ensure system scalability.

Skills

Apache Spark optimization

Machine learning pipeline development

Python programming

Collaboration in Agile environments

Data workflow orchestration

Education

Undergraduate degree in Computer Science or related field

Tools

Apache Airflow

PyTorch

ClickHouse

Job description

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Company Description

Visa is a world leader in payments and technology, with over 259 billion payments transactions flowing safely between consumers, merchants, financial institutions, and government entities in more than 200 countries and territories each year. Our mission is to connect the world through the most innovative, convenient, reliable, and secure payments network, enabling individuals, businesses, and economies to thrive while driven by a common purpose - to uplift everyone, everywhere by being the best way to pay and be paid.

Make an impact with a purpose-driven industry leader. Join us today and experience Life at Visa.

Job Description

What it's all about -

The Payments Foundation Models team is a new, high-impact initiative within Visa's Data Science organization. Based in Cambridge, UK, and working closely with global Visa engineering and product teams, the group's mission is to build the next generation of payments-focused foundation AI models. These models will power a range of premium Risk and Identity Solutions (RaIS) products, such as fraud scores, with the goal of generating more than 100M dollars in new revenue by FY2030, and may be extended into other domains such as credit risk modelling or agentic commerce personalization.

As Senior Consultant Data Engineer you will design, build, optimize, and maintain data tooling and pipelines that power the development and deployment of Visa's Large Transaction Models. You will:

• Design and develop high-performance data pipelines and tooling to support Large Transaction Model training and analysis at global scale.
• Provide technical leadership for your fellow engineers, data scientists and product managers within your Agile Team, and liaise with contributors from other technology and product teams across Visa.
• This is a hands-on technical role in the Individual Contributor track at the Senior Consultant or Senior Manager level, with significant scope to influence engineering standards and practices while working on high-impact, Visa-scale systems.

Key Responsibilities

• Design and develop high-performance data pipelines and tooling to support Large Transaction Model training and analysis at global scale.
• Optimize Spark pipelines and workflows for speed and efficiency across Visa's evolving data warehousing and data analytics infrastructure.
• Provide technical leadership and guidance to other members of the agile team, working with cross-functional stakeholders to align technical solutions with product goals.
• Collaborate with data scientists to build production tooling and pipelines for training PyTorch-based machine learning models.
• Ensure data systems meet Visa's standards for security, reliability, scalability, and compliance.
• Mentor junior engineers and contribute to Visa's software engineering best practices.
• Liaise with global technology and product teams to share tools, patterns, and innovations.
• Drive continuous improvement of team processes and shared workflows.

This is a hybrid position. Expectation of days in the office will be confirmed by your Hiring Manager.

Qualifications

What we'd like from you

• Academic background to at least undergraduate level in a relevant discipline, e.g., Computer Science, Mathematics, Physics, or Engineering.
• Minimum 5 years experience in collaborative software engineering roles.
• Mastery of Apache Spark in large scale, distributed computing environments.
• Proven track record of optimizing Spark queries for performance at scale.
• Familiarity with typical patterns and trade offs in columnar file formats (eg: Parquet), open table formats (eg: iceberg) and analytical query engines.
• Strong experience building and maintaining machine learning pipelines.
• Familiarity with modern software engineering principles and practices (e.g. agile, clean code, IDEs, source control, testing, code review).
• Familiarity with PyTorch models and their integration into production systems.
• Proficiency with data workflow orchestration tools (e.g., Airflow, Luigi, or equivalent).
• Strong programming skills in Python.
• Experience working in Agile or Scrum environments and communicating with non technical stakeholders.
• Background in payments or financial services data engineering.
• Experience in a technical leadership or management role.
• Familiarity with a systems programming language (eg: C++ or Rust).
• Experience with Click house.
• Familiarity with inference optimizations for deep learning models.
• Experience with cloud-based big data platforms (e.g., AWS EMR, GCP Dataproc, Azure HDInsight , Databricks).
• Exposure to MLOps practices and tools.

Additional Information

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.