×
Register Here to Apply for Jobs or Post Jobs. X

Global Head of Data Enablement, SVP

Job in Princeton, Mercer County, New Jersey, 08544, USA
Listing for: State Street Corporation
Full Time position
Listed on 2026-06-22
Job specializations:
  • IT/Tech
    Data Engineering, Data Science Manager
Salary/Wage Range or Industry Benchmark: 225000 - 337500 USD Yearly USD 225000.00 337500.00 YEAR
Job Description & How to Apply Below
Who we are looking for

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.

What you will be responsible for

Field Deployment Engineering & Business Partnership

* 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

Platform Adoption & Value Realization

* 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

Reusable Data Assets & Data Product Adoption

* 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

Use Case Enablement & Delivery Acceleration

* 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

Developer & Data User Enablement

* 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

Feedback Loop to Platform & Architecture 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

Standardization & Scalable Deployment Patterns

* 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

Cross-Functional Collaboration

* 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

Team Leadership

* 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

Qualifications & Experience

* Senior leadership experience in:

* Field engineering, solution engineering, or platform enablement roles

* Large-scale data or platform environments

* Strong technical background in:

* Data platforms and data engineering

* Cloud and distributed systems

* Proven ability to:

* Work deeply with business stakeholders

* Translate platform capabilities into business outcomes

* Experience in financial services or complex enterprise environments preferred

Leadership Profile

* Customer- and business-oriented engineering leader

* Strong communicator able to bridge business and technology

* Pragmatic problem-solver with execution focus

* Skilled at driving adoption and behavioral change at scale

* Collaborative leader who thrives in cross-functional environments

Salary Range:

$225,000 - $337,500 Annual

The range quoted above applies to the role in the primary location specified. If the candidate would ultimately work…
To View & Apply for jobs on this site that accept applications from your location or country, tap the button below to make a Search.
(If this job is in fact in your jurisdiction, then you may be using a Proxy or VPN to access this site, and to progress further, you should change your connectivity to another mobile device or PC).
 
 
 
Search for further Jobs Here:
(Try combinations for better Results! Or enter less keywords for broader Results)
Location
Increase/decrease your Search Radius (miles)
0
200
Filters
Education Level
Experience Level (years)
Posted in last:
Salary