Proven leadership in enterprise data products and analytics
Ability to link data investments to business outcomes
Experience with multidisciplinary technical teams
Strong grasp of modern data architecture and Data Mesh
Hands-on technical leadership with rapid prototyping skills
Responsibilities
Lead the Information Delivery & Intelligence portfolio and team
Establish data-product inventory and delivery plans
Deliver production-ready data products for client servicing
Translate business priorities into reusable data products
Partner with various teams to enhance adoption and consumption
Track delivery, adoption, and business value of datasets
Drive adoption of Eliza Mesh and develop AI-enabled capabilities
Benefits
Opportunity to lead a multidisciplinary team
Engagement with cutting-edge data technologies
Focus on innovation and value realization
Collaborative work environment with cross-functional teams
Potential for significant impact on client experience and operational effectiveness
Full Job Description
Job Description
We're seeking a future team member for the role of Senior Director - Information Delivery & Intelligence to join our Asset Servicing team. This role is located in NYC, NY.
In this role, you'll make an impact in the following ways:
Our Team
Asset Servicing is building trusted, reusable and AI-ready data products that improve client experience, support commercial growth and enable more intelligent operations.
The Information Delivery & Intelligence team is responsible for delivering strategic data products through ODS, Vault, APIs and other approved channels, while demonstrating their value through analytics, business intelligence and AI-enabled use cases.
Job Summary
We are seeking a Senior Director to lead the Information Delivery & Intelligence pillar across Asset Servicing.
This leader will own the portfolio, roadmap and team responsible for delivering trusted data products, enabling modern information delivery and developing high-impact analytics and AI use cases.
The successful candidate will combine commercial judgment, technical leadership and delivery discipline. Success will be measured through implemented capabilities, active adoption and measurable client, commercial and operational outcomes.
Key Responsibilities
Lead the Information Delivery & Intelligence portfolio, roadmap, team and delivery commitments.
Establish the Asset Servicing data-product inventory and delivery plans across ODS, Vault, APIs, the marketplace and other approved channels.
Deliver standardized, canonical and production-ready data products that support client servicing, reporting, revenue realization and operational measurement.
Translate business priorities into reusable data products and cross-platform information capabilities.
Partner with Product, Operations, Client Service, Channels and Engineering to accelerate adoption and active consumption.
Track delivery, adoption, business value and retirement of redundant datasets and legacy delivery paths.
Intelligence, Mesh and AI Enablement
Drive adoption of Eliza Mesh across Asset Servicing platforms and data products.
Develop cross-platform information products, analytics and AI-enabled capabilities that address high-value business and client needs.
Lead lighthouse use cases that demonstrate commercial value, improve client experience or increase operational effectiveness.
Build the business context and semantic capabilities required for intelligent search, copilots, agents and decision support.
Partner with platform teams to incubate use cases and transition mature capabilities into the appropriate platform operating model.
Governance-by-Design and Production Readiness
Embed metadata, data quality, lineage, enterprise keys and data contracts into data-product delivery workflows.
Automate registration, certification and control evidence to reduce manual governance effort.
Establish production-readiness requirements covering monitoring, service expectations, issue routing and support.
Partner with Data Operations and Platform Data Leaders to identify control gaps, assign remediation owners and track completion.
Build reusable onboarding and integration patterns that accelerate delivery into Eliza Mesh and strategic information channels.
Leadership Responsibilities
Lead and develop a multidisciplinary team spanning data-product delivery, Mesh integration, marketplace enablement, business intelligence, data science and delivery execution.
Set priorities and hold the team accountable for delivery, adoption and measurable business outcomes.
Maintain clear ownership boundaries between enterprise enablement and platform-specific responsibilities.
Communicate progress, risks, dependencies and investment needs to senior leadership.
Build a culture focused on implementation, automation, experimentation and value realization.
To be successful in this role, we're seeking the following:
Bachelor's degree or equivalent combination of education and experience.
15+ years of experience in the finance industry.
Proven experience leading enterprise data products, information platforms, analytics or digital capabilities.
Demonstrated ability to connect data investments to commercial, client and operational outcomes
Experience leading multidisciplinary technical and product teams.
Strong understanding of modern data architecture, Data Mesh, cloud platforms and information-delivery patterns.
Experience translating business problems into scalable, production-ready capabilities.
Knowledge of metadata, lineage, data quality, enterprise identifiers and data contracts.
Experience delivering analytics-ready, AI-ready or customer-facing data capabilities.
Demonstrated ability to move capabilities from concept through production and sustained adoption.
Strong executive communication and stakeholder-management skills.
The role requires hands-on technical leadership and the ability to challenge designs and support rapid prototyping. It is not a strategy, PMO or coordination position
Technical Experience Strongly Preferred:
Snowflake, Databricks and modern cloud-data platforms
ODS, data products and Data Mesh architectures
Python, SQL, APIs and workflow automation
Metadata, lineage and data-catalog technologies
Business intelligence, analytics and semantic layers
AI, semantic search, vector databases and enterprise-intelligence solutions
CI/CD pipelines, event-driven integration and production monitoring
