SVP, Enterprise Data Architecture & Data Assets

State Street; Princeton (NJ); On-site; USD 180,000 - 280,000; Full time

Job summary

State Street in Princeton, New Jersey seeks a visionary Head of Data Architecture to define a unified enterprise data architecture and a multi-year transformation roadmap enabling AI-ready data across the organization. You will orchestrate across business and technology to create a cohesive view that aligns with strategic objectives and data governance standards.

In this role, you will standardize data assets, domain definitions, and data flows, driving adoption of reusable data products and

Qualifications

• Experience leading enterprise data architecture initiatives.
• Strong collaboration across business and technology functions.
• Ability to translate business domain complexity into standardized data models.
• Knowledge of data governance, data quality, and metadata management.
• Experience with data products and a reuse-first design approach.
• Excellent communication and stakeholder management skills.

Responsibilities

• Define and maintain the enterprise data architecture vision and target state.
• Develop a unified 'One State Street' data architecture blueprint across domains and platforms.
• Build deep understanding of business processes, domain data models, and data usage.
• Translate domain complexity into standardized enterprise data models and structures.
• Define a multi-year data architecture roadmap and transformation sequence.
• Ensure architecture is actionable, measurable, and aligned with strategy.

Job description

State Street in Princeton, New Jersey seeks a visionary Head of Data Architecture to define a unified enterprise data architecture and a multi-year transformation roadmap enabling AI-ready data across the organization. You will orchestrate across business and technology to create a cohesive view that aligns with strategic objectives and data governance standards.

In this role, you will standardize data assets, domain definitions, and data flows, driving adoption of reusable data products and