Global Head of Data Enablement, SVP

• Promote reuse-first data consumption patterns
• Identify gaps in reusable data availability
• Data Architecture

Lead enterprise-wide Field Deployment Engineering for Data Platforms, partnering directly with businesses to deliver outcomes by driving adoption, deployment, and effective use of enterprise data platforms and reusable data assets.

The Head of Data Platform Enablement is accountable for ensuring that State Street’s data platforms are successfully deployed, adopted, and delivering measurable business outcomes across all lines of business.

This role leads a Field Deployment Engineering organization that works closely with businesses to translate platform capabilities into real business value.

Unlike platform engineering roles, this function is deeply embedded with business teams to:

• Accelerate platform adoption
• Solve real-world implementation challenges
• Drive effective use of reusable data products and enterprise datasets

This role serves as the last-mile execution layer, ensuring that enterprise data platforms are not only built correctly, but used effectively and consistently across the firm.

Success is measured by platform adoption, speed of deployment, reuse of enterprise data assets, and realized business outcomes.

• Lead a global field engineering organization aligned to business domains
• Partner directly with business and technology teams to:
• Deploy data platforms into business use cases
• Solve integration and adoption challenges
• Ensure alignment with business objectives
• Act as a trusted engineering partner to business leaders and domain teams

• Drive adoption of enterprise data platforms across:
• Investment Services
• Investment Management
• Wealth
• Alpha
• Markets
• Control functions
• Ensure platforms are used to deliver:
• Business insights
• Operational efficiencies
• Scalable data capabilities
• Track and improve adoption metrics and business impact

• Drive the use of reusable data assets and enterprise datasets across all businesses
• Ensure consistent consumption of:
• Standardized data definitions
• Shared data products
• Partner with Data Architecture and Data Platform Engineering to:
• Promote reuse-first data consumption patterns
• Identify gaps in reusable data availability

• Enable rapid deployment of data-driven use cases, including:
• Analytics and reporting
• Data products
• AI/ML use cases in partnership with AI Platform Engineering
• Provide hands‑on engineering support to:
• Reduce time to production
• Overcome integration and onboarding challenges
• Accelerate adoption through proven patterns and repeatable approaches

• Improve usability and accessibility of data platforms by:
• Supporting onboarding of engineers, analysts, and business users
• Providing guidance on platform usage and best practices
• Drive a self‑service data consumption model, reducing reliance on centralized teams

• Act as the voice of the user and business back to:
• Data Platform Engineering
• Data Architecture
• Identify:
• Platform gaps
• Usability challenges
• Missing data assets or capabilities
• Ensure continuous improvement of platforms based on real-world usage

• Develop and promote repeatable deployment patterns and playbooks
• Standardize how data platforms are implemented across business domains
• Ensure consistency in how platforms and data products are consumed

• Partner with:
• Data Platform Engineering to enable adoption
• AI Platform Engineering to support AI use case deployment
• Data Architecture to align to domain models
• Data & AI Strategy, Portfolio & Value to align to priorities

• Build and lead a global Field Deployment Engineering organization
• Structure teams aligned to business domains and use case delivery
• Foster a culture of:
• Customer orientation (business‑first mindset)
• Engineering rigor
• Speed and execution discipline

• Senior leadership experience in:
• Field engineering, solution engineering, or platform…