Enterprise Data Architect

The Enterprise Data Architect will define and evolve the enterprise data architecture to support the firm’s business strategy, technology roadmap and product/platform operating model, ensuring data is treated as a strategic asset and is fit for analytics, reporting, operational decisioning and AI use cases.

• Develop and communicate the enterprise data architecture vision and strategy, aligned to business priorities and the technology roadmap, in support of the firms broader data & AI strategy.
• Define and embed the target-state data platform and data product architecture (including metadata, lineage and governance) that enables trusted analytics and AI/ML (e.g., feature reuse, RAG-ready knowledge assets).
• Be accountable for the data architecture within the enterprise data platform, ensuring it remains coherent, scalable and aligned to enterprise standards (e.g., data modelling, metadata/lineage, security and governance).
• Define, embed and govern lakehouse patterns such as medallion architecture (bronze/silver/gold), including ingestion, refinement, quality controls and promotion of curated datasets/data products.
• Define, embed and help implement the data product operating model (domain ownership and stewardship, data product lifecycle, data contracts, and data SLAs/SLOs) to enable reuse and accountability across the firm, in collaboration with the Data Governance & Enablement Team.
• Define and embed decision rights and RACI for enterprise data architecture and data products (e.g., ownership, approval and escalation paths across domains, platform teams, Data Governance & Enablement and other stakeholders).
• Create and maintain a high-level roadmap for evolving enterprise data capabilities (data quality, master/reference data, analytics and AI enablement), including transitional architectures.
• Define, embed and govern enterprise standards, patterns and reference architectures (data modelling, data integration, data products, semantic layers and AI data/knowledge patterns) to ensure consistency, interoperability and reuse.
• Engage key stakeholders (Information Security, Office of the General Counsel, and the Data Governance & Enablement Team) to ensure architecture choices meet security, privacy, regulatory and governance requirements.

This role owns the enterprise data architecture (data domains, models, data products, semantics, governance requirements and AI data/knowledge patterns). Enterprise Integration Architecture owns the integration strategy and design for moving data between systems (integration patterns, middleware, APIs/eventing, orchestration and interface standards). The Enterprise Data Architect partners with Enterprise Integration Architecture to ensure integration designs correctly implement the target data architecture, data quality, lineage, security and compliance controls end-to-end.

The role will also partner with delivery teams to turn strategy into outcomes, providing thought leadership, practical guidance and solution direction. Working closely with Data & AI colleagues and fellow architects (Business, Enterprise and Enterprise Integration), the Enterprise Data Architect helps shape investment choices, ensures solutions align to enterprise principles, and promotes responsible, secure and scalable use of data for analytics and AI.

The role provides clear guardrails and an architecture runway for teams, favouring early engagement and enablement over late-stage approvals.

• Lead architecture governance and design assurance for data, analytics and AI solutions against enterprise principles, working alongside Business, Enterprise, Integration, Cloud and Solution Architects to align end‑to‑end design.
• Support platform and product owners with live environment compliance reporting, including data controls that support Responsible AI (e.g., lineage, data quality, access, retention) and model‑operational readiness.
• Partner with Product and Platform leadership, in collaboration with the Data & AI team, to embed data product ways of working (prioritisation, backlogs, funding/investment cases, and OKRs/KPIs) and to…