Senior Vice President, POM Product Management

BNY Mellon•New York, NY

1h•$104,000 - $200,000•Onsite

About The Position

We’re seeking a future team member for the role of Senior Vice President, Product Manager, Data Solutions & Services. This role is located in New York City. In this role, you’ll make an impact by defining and executing the product strategy for enterprise data capabilities, aligning the roadmap to DSS priorities, platform needs, business outcomes, and the firm’s broader data and AI strategy. You will advance DSS’s five strategic pillars by improving resiliency through modernization, data quality, governance, accessibility through Data Mesh, and commercial value through reusable Data Products. You will own the product roadmap for increasing enterprise consumption of authoritative data masters, including Unified Client Master, Unified Product Master, Security Master, and related reference-data capabilities. You will partner with platforms and hubs to identify where local, fragmented, or duplicative data sources remain in use and develop practical migration and adoption plans toward authoritative enterprise masters. You will convert platform adoption barriers into prioritized product requirements, backlogs, milestones, ownership, dependencies, acceptance criteria, and measurable delivery outcomes. You will support modernization by identifying product priorities that strengthen resilience, reduce dependency on legacy data infrastructure, simplify integration patterns, and improve the reliability of foundational data services. You will define product capabilities that improve data quality, issue detection, triage, remediation, feedback loops, and accountability for data at its source. You will support governance embedding ownership, lineage, metadata, data-quality standards, permissible-use expectations, and governance requirements into product design and delivery. You will support data Mesh by making governed enterprise data easier to register, certify, discover, access, and reuse across reporting, analytics, business applications, and AI-enabled solutions. You will support commercial value by identifying reusable data-product opportunities, validating demand, defining target consumers, connecting products to measurable use cases, and tracking adoption and realized benefits. You will shape product capabilities such as APIs, events, self-service onboarding, reusable integration patterns, reference implementations, and implementation guidance that make authoritative data easier for platforms to consume. You will define and track product measures at the platform and application level, including master-data consumption, adoption progress, data-product usage, implementation milestones, service performance, and business outcomes. You will partner across Product, Engineering, Architecture, Data Operations, Governance, Risk, Finance, and business teams to align investment, sequencing, delivery capacity, controls, and adoption commitments. You will lead the full product lifecycle from discovery and prioritization through delivery, release, adoption, performance measurement, and continuous improvement. You will communicate strategy, progress, value, risks, dependencies, and decisions through concise, data-driven materials for senior business and technology stakeholders. You will act as a senior product leader and trusted advisor, influencing platforms and hubs that consume DSS capabilities without directly owning their engineering resources.

Requirements

Bachelor’s degree required or equivalent experience required.
8–10+ years of product management, data-product, platform-product, or related technology-delivery experience.
Experience managing product roadmaps and end-to-end delivery in a complex enterprise environment.
Strong understanding of enterprise data platforms, master/reference data, APIs, governance, and data quality.
Demonstrated ability to influence senior stakeholders and lead cross-functional execution.

Nice To Haves

Financial services or other regulated-industry experience is preferred.

Responsibilities

Define and execute the product strategy for enterprise data capabilities, aligning the roadmap to DSS priorities, platform needs, business outcomes, and the firm’s broader data and AI strategy.
Advance DSS’s five strategic pillars by improving resiliency through modernization, data quality, governance, accessibility through Data Mesh, and commercial value through reusable Data Products.
Own the product roadmap for increasing enterprise consumption of authoritative data masters, including Unified Client Master, Unified Product Master, Security Master, and related reference-data capabilities.
Partner with platforms and hubs to identify where local, fragmented, or duplicative data sources remain in use and develop practical migration and adoption plans toward authoritative enterprise masters.
Convert platform adoption barriers into prioritized product requirements, backlogs, milestones, ownership, dependencies, acceptance criteria, and measurable delivery outcomes.
Support modernization by identifying product priorities that strengthen resilience, reduce dependency on legacy data infrastructure, simplify integration patterns, and improve the reliability of foundational data services.
Define product capabilities that improve data quality, issue detection, triage, remediation, feedback loops, and accountability for data at its source.
Support governance embedding ownership, lineage, metadata, data-quality standards, permissible-use expectations, and governance requirements into product design and delivery.
Support data Mesh by making governed enterprise data easier to register, certify, discover, access, and reuse across reporting, analytics, business applications, and AI-enabled solutions.
Support commercial value by identifying reusable data-product opportunities, validating demand, defining target consumers, connecting products to measurable use cases, and tracking adoption and realized benefits.
Shape product capabilities such as APIs, events, self-service onboarding, reusable integration patterns, reference implementations, and implementation guidance that make authoritative data easier for platforms to consume.
Define and track product measures at the platform and application level, including master-data consumption, adoption progress, data-product usage, implementation milestones, service performance, and business outcomes.
Partner across Product, Engineering, Architecture, Data Operations, Governance, Risk, Finance, and business teams to align investment, sequencing, delivery capacity, controls, and adoption commitments.
Lead the full product lifecycle from discovery and prioritization through delivery, release, adoption, performance measurement, and continuous improvement.
Communicate strategy, progress, value, risks, dependencies, and decisions through concise, data-driven materials for senior business and technology stakeholders.
Act as a senior product leader and trusted advisor, influencing platforms and hubs that consume DSS capabilities without directly owning their engineering resources.