Senior Data Architect- London, Bristol, Edinburgh

FDM is a global business and technology consultancy seeking a Senior Data Architect to work for our client within the Financial Services sector. This is initially a 6-12- month contract with the potential to extend and will be a hybrid role that will be based in London, Bristol or Edinburgh.

Our client is seeking an experienced Data Architect with a strong focus on AI-enabled solutions to lead the design, governance, and evolution of enterprise data architectures supporting advanced analytics, machine learning, and fraud prevention initiatives.

The successful candidate will have proven experience architecting modern data platforms that underpin AI capabilities, with particular expertise in fraud detection, risk management, and intelligence-led environments. They will possess deep knowledge of Microsoft's data, security, and governance ecosystem and be responsible for ensuring data platforms are scalable, secure, compliant, and optimised for AI workloads.

Responsibilities:

Data Architecture & Strategy

• Design and implement enterprise-scale data architectures that support AI, machine learning, and advanced analytics capabilities.
• Develop data models, data flows, integration patterns, and architecture standards aligned with business objectives.
• Define and maintain target-state data architecture roadmaps supporting organisational transformation initiatives.
• Establish best practices for data storage, processing, governance, and consumption.

AI & Advanced Analytics Enablement

• Architect data platforms that support AI and Generative AI solutions.
• Collaborate with Data Scientists, AI Engineers, and Platform Teams to deliver scalable AI-ready data environments.
• Ensure data architectures support model training, inference, monitoring, and responsible AI practices.
• Enable real-time and batch analytical workloads required for predictive fraud detection and risk management.

Fraud & Risk Management

• Design data solutions supporting fraud detection, investigation, prevention, and intelligence gathering.
• Work with fraud operations, risk, and compliance teams to understand data requirements and operational challenges.
• Implement architectures capable of handling high-volume transactional data and complex analytical processing.
• Support the development of fraud analytics models through the provision of high-quality, governed datasets.

Governance, Security & Compliance

• Establish enterprise data governance standards and frameworks.
• Ensure compliance with data protection regulations and internal security policies.
• Implement data classification, retention, lineage, and auditing capabilities.
• Embed security-by-design principles across all data solutions.

Stakeholder Engagement

• Provide architectural leadership and technical guidance across business and technology teams.
• Produce architecture documentation, design artefacts, and governance assessments.
• Present architectural recommendations to senior stakeholders and governance boards.
• Support delivery teams through architecture reviews and technical assurance activities.