Vice President, Product Management - Data Platform

Our Purpose

Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential.

Title and Summary

Vice President, Product Management - Data Platform

Overview

The Vice President, Product Management is responsible for defining and delivering the product strategy, roadmap, and outcomes for an enterprise, cloud-native data platform that enables a federated data mesh across the organization. This platform serves as the foundation for analytics, AI/ML, data products, and data commercialization use cases at scale.
In this role, you will lead a portfolio of platform capabilities—including data ingestion, storage, processing, platform observability and FinOps—designed to empower domain teams to own and publish high-quality data products while maintaining enterprise-grade security, compliance, and reliability.

You will work closely with Engineering, Architecture, Product Operations, Finance, and Business stakeholders to ensure the platform enables self-service, scalability, and innovation while aligning with enterprise standards and strategic objectives.
Key Responsibilities

Product Strategy & Vision
• Define and evolve the product vision and strategy for the enterprise data platform supporting a federated data mesh.
• Articulate a clear target state for the platform, aligned to enterprise data, analytics, and AI strategies.
• Translate business and domain needs into scalable platform capabilities and services.

Roadmap & Capability Ownership
• Own the platform product roadmap, including prioritization of capabilities such as:
• Data ingestion and integration (batch, streaming, source connectors)
• Data Lakehouse and analytical storage
• Orchestration framework (airflow patterns), transformation libraries, data contracts, etc.
• Platform SLOs, Reliability engineering, Usage analytics, etc.
• Cost attribution & chargeback (including forecasting)
• Balance near-term delivery with long-term architectural integrity and scalability.

Data Mesh Enablement
• Enable domain teams to operate as data product owners by providing clear standards, tooling, and self-service capabilities.
• Partner with Data Governance to embed federated governance and policy enforcement into the platform.
• Ensure the platform reduces friction while maintaining enterprise guardrails.

Cross-Functional Leadership
• Partner with Engineering to translate product requirements into executable technical plans.
• Collaborate with Product Operations on adoption, enablement, and customer experience.
• Work with Architecture, Security, Legal, and Risk teams to ensure platform compliance and resilience.
• Influence without direct authority across distributed, global teams.

Delivery & Execution
• Ensure platform capabilities are delivered with a strong focus on quality, reliability, and readiness for enterprise-scale launch.
• Define success metrics and ensure outcomes align to business and platform goals.
• Drive continuous improvement through customer feedback, usage insights, and performance data.

Stakeholder Engagement & Communication
• Serve as the primary product leader and evangelist for the data platform.
• Build strong relationships with senior executives and domain leaders.
• Communicate platform value, roadmap progress, and outcomes in clear, executive-ready language.

Skills & Experience
Required Qualifications
• Proven experience in Product Management, with significant experience leading enterprise platform products.
• Proven experience building or scaling cloud-native data platforms or large-scale analytics platforms.
• Deep understanding of data mesh concepts, including domain ownership, data products, federated governance, and self-service infrastructure.
• Experience with modern data technologies and ecosystems, such as:
• Cloud platforms (AWS, Azure, GCP)
• Lakehouse and analytics platforms (e.g., Databricks, Snowflake)
• Streaming, APIs, and event-driven architectures
• Strong analytical and systems-thinking skills.

Preferred Qualifications
• Experience in highly regulated industries such as financial services, pay