Director, Data Engineering

Mastercard
Dublin, IrelandPosted 9 May 2026

Job Description

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 Director, Data Engineering Overview: 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. This is an exciting opportunity for you to join Mastercard’s Financial Crime Solutions program driving greatness in the crypto & digital asset fraud prevention and anti-money laundering space. You will be responsible for the analysis, design, development and delivery of some of our newest in-house built initiatives. What you will do: • Set and execute a near- and mid-term data engineering strategy, aligning priorities to organizational goals and raising the bar on delivery, quality, and operational excellence. • Lead the analysis, architecture, design, and delivery of complex data solutions that meet business needs, reliability targets, and quality standards. • Partner across Engineering, Product, Data Science, Platform, and Integration teams to define target architectures and pragmatic implementation plans. • Build and communicate a data roadmap that balances new capabilities with platform health - including reliability, scalability, and cost effectiveness. • Provide technical leadership on design reviews, code and pipeline reviews, and coaching that embeds best practices and strong engineering fundamentals. • Champion data quality, security, privacy, and compliance across the end-to-end data lifecycle. • Translate business outcomes into scalable data products by collaborating with Product Owners, Product Managers, Data SMEs, and stakeholders. • Enable advanced analytics and machine learning use cases by partnering closely with Data Scientists and the broader data platform community. • Evaluate and recommend technology investments that improve pipeline efficiency, observability, reliability, and time-to-data. • Influence and advance data governance and quality practices, partnering with peers to standardize patterns that scale. • Lead and grow leaders and senior individual contributors: set goals, coach and mentor, develop top talent, and build a culture of continuous improvement, inclusion, and accountability. • Role-model the Mastercard Way through your day-to-day leadership - recognition, coaching, and employee engagement. • Attract, hire, and retain exceptional talent; building teams that are stronger with every hire. All about you • A people-first leader with a strong hands-on foundation in modern data engineering and architecture; and a genuine desire to shape what great looks like. • A track record of inspiring teams to think end-to-end, connect daily work to enterprise impact, and deliver outcomes that matter. • Experience building and scaling high-performing teams, strengthening collaboration across disciplines, and creating clarity in complex environments. • A delivery mindset: you mobilize people with speed and accountability, stay relentlessly customer-focused, and turn ambiguity ... (truncated, view full listing at source)
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