Senior Analyst Product Manager - Enterprise Data Enablement

About the role

The AI & Data Governance team at Mastercard is looking for a Technical Product Manager to help build, scale and improve its enterprise data products. The role works across business, product, engineering, analytics and platform teams to turn needs into clear requirements and delivery plans, and strengthens product operations through better documentation, planning, reporting, adoption support and AI-enabled automation.

Key responsibilities

• Manage data products from intake and discovery through delivery, launch, adoption, measurement and ongoing improvement.
• Work with business, product, engineering, analytics, architecture and platform teams to align priorities, requirements, dependencies and outcomes.
• Maintain roadmaps, backlogs, release plans, risks, decisions and stakeholder communications.
• Review new data needs against existing products, improve documentation, encourage reuse, reduce duplication and identify product gaps.
• Create metrics, dashboards, reporting and enablement materials showing progress, adoption, product health, risk and business impact.
• Use AI and automation to simplify product operations, and partner with governance, privacy, risk, security and compliance teams to build required controls into the process.

Required profile

• Product mindset with experience supporting technical, data, analytics, platform or enterprise technology products from discovery through delivery and measurement.
• Comfortable with data concepts such as data products, data contracts, metadata, lineage, data quality, semantic models, analytics use cases and modern data platforms.
• Uses data, metrics, dashboards and adoption signals to find patterns and guide product decisions.
• Communicates clearly with technical and non-technical audiences and turns complex topics into simple business language.
• Organized, self-directed and able to work through ambiguity while building alignment and taking ownership.

Preferred capabilities

• Experience with enterprise data products, analytics products, shared data services or modern data platform capabilities.
• Product and delivery tools such as Aha, Jira, Monday.com or similar.
• Understanding of platforms such as Microsoft Fabric, Power BI, Dataverse, Power Platform, Databricks, Atlan, Collibra, Microsoft Purview, APIs, integrations, workflow automation and intelligent agents.
• Adoption plans, training, release communications, product playbooks and analytics using SQL, Excel, Power BI, Python or comparable tools.