Senior Analyst Product Manager - Enterprise Data Enablement

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

Senior Analyst Product Manager - Enterprise Data Enablement

Who is Mastercard?

Mastercard is a global technology company in the payments industry. Our mission is to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart, and accessible. Using secure data and networks, partnerships and passion, our innovations and solutions help individuals, financial institutions, governments, and businesses realize their greatest potential.

Our decency quotient, or DQ, drives our culture and everything we do inside and outside of our company. With connections across more than 210 countries and territories, we are building a sustainable world that unlocks priceless possibilities for all.

Role

The AI & Data Governance team is looking for a Technical Product Manager to help build, scale, and improve Mastercard’s enterprise data products.

In this role, you will help make data products easier to find, understand, use, and improve. You will work across business, product, engineering, analytics, and platform teams to turn needs into clear requirements and practical delivery plans.

You will also help strengthen product operations by improving documentation, planning, reporting, adoption support, and AI-enabled automation that reduces manual work and improves decision-making.

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 so work is clear and well coordinated.

Review new data needs against existing products, improve product documentation, encourage reuse, reduce duplication, and identify product gaps.

Create metrics, dashboards, reporting, and enablement materials that show progress, adoption, product health, risk, business impact, and help teams use data products effectively.

Use AI and automation to simplify product operations while partnering with governance, privacy, risk, security, and compliance teams to build required controls into the process.

All About You

You bring a product mindset, with experience supporting technical, data, analytics, platform, or enterprise technology products from discovery through delivery and measurement.

You are comfortable working with data concepts such as data products, data contracts, metadata, lineage, data quality, semantic models, analytics use cases, and modern data platforms.

You use data, metrics, dashboards, adoption signals, and product health indicators to find patterns, develop insights, and guide practical product decisions.

You communicate clearly with technical and non-technical audiences and can turn complex topics into simple, useful business language.

You are organized, self-directed, and comfortable working through ambiguity while building alignment, taking ownership, and simplifying complexity.

Preferred Capabilities

You have worked with enterprise data products, analytics products, shared data services, or modern data platform capabilities.

You can use product and delivery tools such as Aha, Jira, Monday.com, or similar platforms to manage intake, planning, backlogs, delivery tracking, and reporting.

You understand how platforms such as Microsoft Fabric, Power BI, Dataverse, Power Platform, Databricks, Atlan, Collibra, Microsoft Purview, APIs, integrations, workflow automation, intelligent agents, or similar tools support data product delivery, adoption, and operational improvement.

You can create practical adoption plans, training, release communications, product playbooks, office hours, scalable support processes, and analytics using tools such as SQL, Excel, Power BI, Python, or comparable technologies.

Corporate Security Responsibility

All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must:

• Abide by Mastercard’s security policies and practices;

• Ensure the confidentiality and integrity of the information being accessed;

• Report any suspected information security violation or breach, and

• Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.