Join Mastercard's Foundational Data & Model Services team as a Senior Technical Program Manager and play a pivotal role in shaping the future of data and AI foundations. This is an exciting opportunity to influence the roadmap of a newly formed team, driving critical data initiatives. You will be instrumental in managing the transition from legacy Hadoop and on-prem ETL systems to modern Databricks architecture.

Mastercard is dedicated to powering economies and empowering individuals globally, fostering a sustainable economy where everyone can thrive. We are committed to providing secure, simple, and smart digital payment solutions, leveraging our technology, innovation, and partnerships to help businesses and governments reach their full potential.

As a Senior Technical Program Manager, you will orchestrate delivery across multiple squads, meticulously managing interdependencies with platform, product, and central teams. Your key responsibilities include:

- Ensuring the successful adoption of shared data models and pipelines across various product teams. - Leading the migration from Hadoop and on-prem ETL to Databricks, overseeing sequencing, cutover, and decommissioning of legacy systems. - Maintaining visibility of the legacy platform's operational needs within the migration plan to prevent disruption to live services. - Facilitating engagement with central platform, cloud operations, and data governance teams to resolve cross-functional dependencies. - Managing vendor and partner relationships, ensuring alignment on roadmaps and performance against commitments. - Applying technical acumen to evaluate data modeling, pipeline design, and data quality decisions, translating trade-offs effectively for business stakeholders. - Establishing planning and reporting cadences for the new team, including intake processes, prioritization frameworks, and leadership reporting.

We are seeking a seasoned professional, and we encourage applications even if not all criteria are met. Ideal candidates will possess:

- Proven experience managing technical programs within data engineering, data platforms, or analytics infrastructure. - Robust understanding of both legacy (Hadoop, Hive, ETL) and modern (Databricks, Spark, Airflow) data technologies, with strong SQL proficiency for scope definition and risk identification. - Expertise in platform migrations where maintaining live operations of the legacy system is crucial. - Deep knowledge of data modeling principles, including schemas, lineage, and common definitions, and their downstream impact. - Familiarity with data governance, access control, and handling sensitive customer data in regulated environments. - A demonstrated ability to drive adoption of shared platforms through persuasion, evidence, and consistent follow-through. - Comfort navigating ambiguity, developing credible plans with incomplete information, and adapting plans without viewing changes as failures.