Global Head of Data Architecture, SVP

Who we are looking for Define and establish a unified “One State Street” data architecture , including enterprise data domains, reusable data assets, and a clear multi-year roadmap—enabling consistent, AI-ready data across all businesses and functions. The Head of Data Architecture is accountable for creating a cohesive enterprise data architecture that spans State Street’s full business landscape, including: Investment Services Investment Management Wealth Alpha platform Global Markets Corporate and control functions This role works deeply across business and technology to understand domain-level data structures, flows, and usage , and synthesize them into a single, integrated enterprise architecture view . A core focus is to identify, standardize, and drive adoption of reusable data assets and enterprise definitions , ensuring that the organization benefits from shared, consistent, and high-quality data across use cases, platforms, and business lines. The role defines both the target-state architecture and the practical transformation journey , ensuring that current fragmented data landscapes evolve into a well-structured, scalable, and AI-ready ecosystem. Success is measured by clarity and adoption of enterprise data architecture, reuse of data assets across domains, and enablement of scalable data and AI platforms . What you would be responsible for Enterprise Data Architecture Vision & “One State Street” Blueprint Define and maintain the enterprise data architecture vision and target state Develop a unified “One State Street” data architecture blueprint , integrating: All business domains Cross-functional data flows Platform-aligned data structures Create clear architectural representations that simplify the enterprise data landscape Deep Business Domain Alignment Partner closely across: Investment Services Investment Management Wealth Alpha platform Global Markets Control functions (Finance, Risk, Compliance, Operations, etc.) Build deep understanding of: Business processes Domain data models Data usage and dependencies Translate domain complexity into standardized enterprise data models and structures Enterprise Data Domains & Modeling Define and standardize: Enterprise data domains and sub-domains Domain ownership boundaries Conceptual and logical data models Ensure consistency and interoperability across domains Enable domain-oriented architecture aligned to modern principles (e.g., data products and reuse-first design) Reusable Data Assets & Enterprise Definitions Lead identification and standardization of reusable data assets across the firm Define and promote enterprise-level data definitions and canonical data structures Drive reuse of: Core data entities (e.g., client, instrument, transaction, position) Data products and datasets Partner with Data Platform Products (Role 4) to ensure reusable assets are: Easily discoverable Accessible and consumable Drive adoption across businesses to maximize enterprise value from shared data Data Asset Mapping, Classification & Transparency Establish a comprehensive view of enterprise data assets across all domains Define consistent frameworks for: Data asset classification Domain tagging Business vs. technical metadata Ensure visibility into: What data exists Where it resides How it is used Partner with Governance (Role 1) on classification alignment without owning policy Data Architecture Roadmap & Transformation Journey Define a multi-year data architecture roadmap from current to target state Identify: Redundant and fragmented data assets Opportunities for consolidation and reuse Critical architecture gaps Sequence transformation in alignment with: Strategy & Portfolio (Role 2) priorities Platform delivery roadmaps Ensure architecture is actionable and tied to real execution Standards, Patterns & Architectural Guidance Define enterprise standards for: Data design and modeling Data integration and interoperability Data product structure Establish reusable