Senior Data Architect- London, Bristol, Edinburgh

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.

• Extensive experience designing and delivering enterprise data architectures.
• Strong understanding of modern data platform design principles including data lakes, lakehouses, data warehouses, and real-time streaming architectures.
• Experience with large-scale data integration and ETL/ELT frameworks.
• Strong understanding of data modelling methodologies and information architecture.

AI & Machine Learning

• Experience architecting data platforms that support AI, machine learning, and advanced analytics solutions.
• Understanding of AI lifecycle requirements, feature engineering, model deployment, and monitoring.
• Knowledge of responsible AI, model governance, and AI security considerations.

Fraud & Financial Crime

• Demonstrable experience working within fraud, financial crime, risk, cybersecurity, or intelligence-led environments.
• Knowledge of fraud detection techniques, behavioural analytics, anomaly detection, and transaction monitoring.
• Experience supporting fraud analytics, investigation platforms, or risk management solutions.

Microsoft Data Ecosystem

Strong experience across Microsoft's modern data platform, including:

• Microsoft Fabric
• Azure Data Lake Storage (ADLS)
• Azure Databricks
• Azure Synapse Analytics
• Azure Data Factory
• Azure SQL
• Microsoft Purview
• Power BI
• Azure Machine Learning
• Azure OpenAI Services
• Azure AI Services

Security & Governance

Strong understanding of:

• Microsoft Purview
• Microsoft Defender
• Microsoft Entra ID
• Azure Security Centre / Defender for Cloud
• Data governance frameworks
• Data privacy and regulatory compliance
• Data lineage, metadata management, and information protection