Lead Data Architect

Lead the design of enterprise-level logical and physical data models across complex business and operational environments.

• Define data architecture, integration and interoperability standards across multiple systems and data sources.
• Establish reusable architectural patterns for data ingestion, transformation and consumption.
• Own architecture governance and ensure solutions align with enterprise, security and compliance standards.
• Embed strong practices across data quality, MDM, lineage, metadata and data stewardship.
• Develop metadata frameworks, data dictionaries and semantic layers to create consistent and trusted data definitions.
• Design data structures and access patterns optimised for LLMs, Machine Learning and Agentic AI systems.
• Guide Data Engineers and collaborate with AI, Analytics and business teams to translate requirements into scalable architecture.

Desired Candidate Profile

10 12+ years of experience across Data Architecture, Data Modelling, Enterprise Data Design or Data Governance, including experience at Lead or Principal level.

• Proven experience defining and delivering enterprise data architectures across complex, multi-source environments.
• Strong expertise across conceptual, logical and physical data modelling, including dimensional and Data Vault approaches.
• Hands-on experience with cloud platforms such as Azure, AWS or GCP.
• Experience with modern data platforms and lakehouse technologies such as Databricks, Microsoft Fabric or Snowflake.
• Strong knowledge of data integration and interoperability, including APIs and event- driven/streaming architectures.
• Experience with metadata, lineage and governance technologies such as Unity Catalog, Collibra or Alation, alongside MDM platforms.
• Strong SQL and Spark knowledge with experience across relational and NoSQL data environments.
• Experience designing data architectures capable of supporting AI, ML and Agentic AI workloads.
• Experience within financial services, investment organisations or similarly complex enterprise environments would be advantageous.
• Bachelor s or Master s degree in Computer Science, Engineering or a related technical discipline.