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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Global Head of Data Architecture, SVP - **Company:** State Street - **Location:** United States - **Experience:** Expert - **Salary:** $225,000.0 - $337,500.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Data Architecture, Data Infrastructure, Data Integration, Data Sharing, Data Structures, Digital Assets, Logical Data Models, Data Streaming, Enterprise Data Management, Usage Tracking, AI Platforms, Core Data - **Published:** August 14, 2026 - **Apply:** https://www.dice.com/job-detail/f1e85c86-3d87-436a-b30c-748d43bf70de ## About the Role * Senior leadership experience in data or enterprise architecture within financial services * Strong knowledge of State Street-relevant domains: + Custody and fund services + Asset management + Trading and markets + Wealth and client servicing platforms * Deep understanding of: + Modern data architecture patterns + Distributed and platform-based data ecosystems * Proven ability to: + Define enterprise-wide architecture frameworks + Influence across complex, federated organizations * Strong blend of business domain expertise and technical depth Leadership Profile * Enterprise architect with strong business acumen * Able to unify fragmented landscapes into cohesive, simple architectures * Influential leader who drives alignment without direct control * Balances strategic clarity with execution realism * Strong communicator capable of articulating the "big picture" clearly ## Description 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 architecture patterns that enable: + Platform scalability + AI-ready data design * Provide clear guidance to engineering and platform teams without owning delivery Collaboration with Platforms & Technology * Partner deeply with: + Data Platform Products + AI Platform Products + Enterprise architects within GTS * Ensure architecture is: + Technically feasible + Consistent across environments + Scalable for enterprise AI use Enterprise Influence & Alignment * Act as the enterprise authority on data architecture * Drive alignment across business and technology stakeholders * Promote a reuse-first, domain-driven data culture across the firm Team Leadership * Lead a global team of ~10-15 data architects * Build capabilities in: + Domain architecture + Data modeling + Enterprise data design * Foster a culture of: + Deep business engagement + Practical, execution-oriented architecture + High-quality, consistent outputs ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Blueprints for Success: Steering a Global Data & AI Architecture](https://www.wearedevelopers.com/videos/1577-blueprints-for-success-steering-a-global-data-ai-architecture) - [Smart City, Smart Mobility](https://www.wearedevelopers.com/videos/954-smart-city-smart-mobility) - [This App Reached 10,000 Users in One Week. 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