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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.

• 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.

• 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.

• 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).

• 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 (client, instrument, transaction, position)
  • Data products and datasets
• Partner with Data Platform Products to ensure reusable assets are:
  • Easily discoverable
  • Accessible and consumable
• Drive adoption across businesses to maximize enterprise value from shared data.

• 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 on classification alignment without owning policy.

• 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 priorities
  • Platform delivery roadmaps
• Ensure architecture is actionable and tied to real execution.

• 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.

• 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

• 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.

• 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

• 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.

• 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.

$225,000 - $337,500 Annual

• Retirement savings plan (401K) with company match.
• Insurance coverage including basic life, medical, dental, vision, long-term disability, and other optional additional coverages.
• Paid-time off including vacation, sick leave, short-term disability, and family care responsibilities.
• Employee Assistance Program.
• Incentive compensation including eligibility for annual performance-based awards (excluding certain sales roles subject to sales incentive plans).
• Eligibility for certain tax advantaged savings plans.

For a full overview, visit https://hrportal.ehr.com/statestreet/Home.

We consider all qualified applicants for all positions without regard to race, creed, color, religion, national origin, ancestry, ethnicity, age, disability, genetic information, sex, sexual orientation, gender identity or expression, citizenship, marital status, domestic partnership or civil union status, familial status, military and veteran status, and other characteristics protected by applicable law.

It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.

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