Senior Data Engineer, Anti-Fraud Technology

This Senior Data Engineer role sits within Vanguard Europe's Enterprise Security & Fraud (ES&F) team, building advanced, cloud-native data pipelines and real-time systems that protect clients from fraud and financial crime. The position combines hands-on engineering - spanning ELT development, streaming architectures, IaC, testing, deployment, and operations - with close collaboration across product, engineering, and agile teams. It requires deep experience in Python/Java, SQL, AWS, Kafka/Flink, and data transformation frameworks, with an emphasis on high-quality engineering practices, continuous improvement, and innovative problem-solving in a cybersecurity-focused environment.

Senior Data Engineer - Anti-Fraud Technology (Vanguard Europe)

Location: London (Hybrid: Tue - Thu in office, Mon/Fri remote)

Make an impact where it matters most

Vanguard manages more than $11 trillion in assets worldwide, and with that scale comes a deep responsibility: safeguarding our clients from fraud and financial crime. Our Enterprise Security & Fraud (ES&F) team sits at the heart of this mission. We build advanced, cloud-native technology that detects, prevents, and responds to emerging threats across the UK and Europe.

As a Senior Data Engineer, you'll join a highly skilled, cybersecurity-focused development team delivering real-time data pipelines, decisioning systems, and tooling that protect hundreds of thousands of clients. If you want to apply your engineering expertise to problems with genuine societal and financial impact, this is the place to do it.

• Design and implement real-time data pipelines that power fraud detection and operational decision making.
• Build robust ELT workflows from source ingestion through to data presentation for internal stakeholders.
• Develop event-driven solutions using technologies such as Apache Kafka and Apache Flink.

• Write high-quality, testable, maintainable code in Python or Java, with strong SQL capability.
• Contribute to solution design, code reviews, automated testing, and documentation.
• Apply industry-leading engineering standards with a focus on code quality, consistency, and resilience.

• Build and maintain cloud infrastructure using AWS and Infrastructure-as-Code tooling (CloudFormation/Terraform).
• Own deployment and operational support across development, test, and production environments.
• Champion continuous improvement across tooling, processes, and engineering practices.

• Partner closely with developers, product owners, scrum masters, and analysts to ensure data enables an exceptional client experience.
• Participate fully in agile ceremonies including sprint planning, daily scrums, reviews, and retrospectives.

• 5+ years of experience as a data engineer.
• Strong proficiency in Python or Java, SQL, cloud environments (preferably AWS).
• Hands-on experience with Kafka and streaming frameworks such as Flink.
• Proficiency with data transformation tools (PySpark, Pandas).
• Familiarity with data quality frameworks (e.g., Great Expectations).
• Experience with graph databases is a plus.
• Exposure to building cloud infrastructure via IaC.
• Excellent communication skills, able to translate complex topics for technical and non-technical audiences.
• Understanding of agile development; scrum experience preferred.
• A continuous learning mindset and willingness to expand both technical and non-technical skills.
• A degree in a STEM field is beneficial but not required.

• Purposeful work: Every pipeline, every event stream, and every decisioning workflow contributes directly to protecting investors from financial harm.
• Serious scale: Work with high-volume behavioural, transactional, and event-driven datasets across multiple markets.
• Cutting-edge tooling: We invest in cloud-native, real-time, and streaming architectures - this is not legacy data warehousing.
• Strong engineering culture: Thoughtful design, quality code, operational excellence, and continuous improvement are non-negotiable.
• Collaborative environment: Partner daily with security specialists, fraud analysts, architects, and data scientists.

• Technical conversation with senior engineers
• Hands-on coding exercise
• Competency-based interview focused on collaboration, ownership, and problem-solving