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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Vice President, Data Leader Manager - **Company:** The Bank of New York Mellon Corporation - **Location:** New York, NY, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Data Governance, Data Profiling, Metadata, Data Streaming, Enterprise Data Management, Data Strategy, Data Management - **Published:** August 18, 2026 - **Apply:** https://diversityjobs.com/main/sendform/8/8/28176/1/17979671?backUrl=%2Fcareer%2F17979671%2FSenior-Vice-President-Data-Leader-Manager-New-York-New-York ## About the Role * 7-10+ years of experience or equivalent work experience required * Proven experience leading data strategy from concept through execution with a strong track record of delivery. * Significant experience in enterprise data programs, ideally within financial services, with a strong focus on supporting commercial priorities in Payments and Depositary Receipts, including sales, client coverage, product performance, and business growth. * Strong understanding of data governance, metadata, lineage, data quality, controls, and regulatory expectations. * Experience translating governance and remediation priorities into business enablement, reusable data products, and AI-readiness outcomes. * Ability to align data investments to commercial goals, operating efficiency, control outcomes, and platform delivery. * Proven success managing complex cross-functional programs across business, product, technology, risk, controls, privacy, and data stakeholders. * Strong analytical, problem-solving, and execution skills, including experience with Agile delivery and prioritization. * Experience with data governance tooling, data profiling, remediation, and quality improvement practices. * Strong executive communication, stakeholder management, and people leadership skills, with the ability to influence across senior levels and operate strategically and hands-on. ## Description We're seeking a future team member in the role of Depositary Receipts (DR) and Global Payments & Trade (GP&T) Commercial Data Lead to join our Data Management team in New York, NY. This role will shape and execute the DR and GP&T commercial data agenda, combining strong governance and control discipline with a commercial, execution-oriented mandate. The role will lead strategic data workstreams, enable AI-ready and reusable data products, strengthen end-to-end data risk management, and translate data investments into measurable business value across client, product, and commercial priorities. In this role, you'll make an impact in the following ways: Lead strategy execution across DR and GP&T commercial data priorities * Execute the DR and GP&T commercial data strategy in alignment with BNY's enterprise data strategy and evolving Data & AI operating model. * Steer priority data initiatives that support AI-enabled execution, platform delivery, governance, and risk-managed adoption. * Translate business and commercial priorities into a clear execution roadmap, including prioritization, dependencies, milestones, and outcomes. * Run governance and execution forums to oversee planning, escalation, OKRs, risk management, and decision-making. * Lead process re-engineering efforts that improve data flows, reduce manual intervention, and support strategic goals. Drive commercial office and business enablement outcomes * Partner with commercial, product, client, and functional leaders to identify priority data needs that improve client insight, product management, commercialization, and business performance. * Develop reusable and scalable data capabilities that support commercial use cases, management reporting, operational transparency, and opportunity identification. * Connect data investments to measurable business outcomes, including adoption, efficiency, stronger controls, improved client outcomes, and value realization. * Act as a connector across business, data, and technology teams to ensure commercial needs are reflected in strategy and delivery. Drive data projects, transformation, and AI/data product readiness * Sponsor or lead strategic data projects and initiatives across DR and GP&T commercial. * Support enterprise remediation, cross-platform transformation, and modernization efforts where data readiness is critical. * Partner with business and technology stakeholders to define requirements, clarify ownership, and deliver fit-for-purpose capabilities. * Advance AI-ready data products and help scale data and AI responsibilities through a phased implementation approach. Strengthen data foundations, governance, and execution discipline * Define and prioritize critical data in partnership with governance and business leads, aligned to enterprise data management standards. * Establish authoritative datasets, clear ownership, definitions, lineage, quality expectations, and remediation paths. * Improve metadata, lineage, and rationalization practices to increase transparency, reuse, and control effectiveness. * Own readiness and execution risk across the data user journey, coordinating resolution of dependencies, issues, and adoption barriers. * Support completion of data maturity and readiness activities and track actions through closure. Establish a strong control and responsible data use framework * Partner with Data Quality, Data Privacy, Risk, and Controls leads to strengthen data quality, access, protection, and management practices. * Support regulatory readiness and evidence control effectiveness across applicable data obligations. * Enable safe and trusted reuse through strong provenance, permissible use, fit-for-purpose standards, and responsible sharing. * Represent DR / GP&T commercial in enterprise and business data governance forums and contribute to broader data and AI governance discussions. Deliver measurable value * Track progress across governance, remediation, delivery, and business outcomes. * Establish KPIs that demonstrate adoption, reuse, efficiency gains, control improvement, and commercial impact. * Communicate progress, risks, tradeoffs, and value delivered to senior stakeholders. ## Related Videos - [A Data Mesh needs Open Metadata](https://www.wearedevelopers.com/videos/505-a-data-mesh-needs-open-metadata) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Hacking Your Vacation: Using Data for Fun](https://www.wearedevelopers.com/videos/585-hacking-your-vacation-using-data-for-fun) - [Just-in-time Compilation in JVM](https://www.wearedevelopers.com/videos/240-just-in-time-compilation-in-jvm) - [Big Business, Big Barriers? 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