Senior Technical Program Manager

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

Foundational Data & Model Services sits in Data & AI Foundations, inside Business & Market Insights. We own the data that B&MI's analytics and insights products are built on: the pipelines that bring it in, the data models that shape it, and the standards that keep it consistent for everyone downstream. When a product team needs transaction data modelled a particular way, or a new source onboarded, or a definition that means the same thing in two products, that is us.

About half the estate is Hadoop and Hive with on-prem ETL that has been running for years and still serves live products. The other half is Databricks, and we are moving the rest across. The work is two things at once: keeping the old platform reliable while it is still load-bearing, and rebuilding the data models properly on the new one rather than lifting and shifting what is already there.

The team itself is new, brought together from teams that used to sit apart, and the roadmap is still being written. Plenty is undecided. If that reads as an opportunity rather than a risk, you will enjoy this.

Role

You will own the delivery plan across the squads doing this work, and manage the dependencies between them, the platform teams we rely on, and the product teams waiting on us. Specifically, you will:

Own delivery of the shared data models and pipelines that several product teams depend on, where success is adoption rather than features shipped.

Run the migration off Hadoop and on-prem ETL onto Databricks: sequencing, cutover, and actually switching the old thing off.

Keep the legacy platform's operational commitments visible in the plan, so migration work does not quietly starve the systems still in production.

Broker the dependencies we do not control, working with central platform, cloud operations and data governance teams.

Run vendor and partner engagement: roadmap alignment, milestone tracking, performance against commitments.

Bring enough technical depth to challenge decisions on data modelling, pipeline design and data quality, and to explain the trade-offs to business stakeholders without flattening them.

Set how a new team plans and reports: intake, prioritization, cadence, and what leadership sees each month.

All about you

We do not expect any one person to bring all of this, so apply if most of it fits.

Experience running technical programs in data engineering, data platforms or analytics infrastructure.

Working knowledge of the stack on both sides of the migration: Hadoop, Hive and traditional ETL on one side, Databricks, Spark and orchestration tooling such as Airflow on the other. Strong SQL throughout. Enough to scope work and spot risk without an engineer translating every conversation.

Experience of platform migrations where the old system stays live throughout and the decommissioning is the hard part.

Understanding of data modelling and why it matters: schemas, lineage, common definitions, and what breaks downstream when they drift.

Understanding of data governance, access control and handling customer data in a regulated business.

A track record of getting internal teams to adopt shared platforms, which comes down to persuasion, evidence and follow-through rather than mandate.

Comfortable with ambiguity: able to build a credible plan before every input is settled, and to change it without treating that as a failure.

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.