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Salary
≈ $56k – $135k per year (Estimated)
Location
In office (Dublin)
Seniority
Staff
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 6, 2026. First seen by Alion on Oct 6, 2026. Mastercard scores A on the Alion truth index.

Overview
Company
Impact
Profile match
Mastercard is an American payments technology company whose origins date to 1966, when a group of banks formed the Interbank Card Association to compete with BankAmericard. Like its main rival it does not issue cards or extend credit; it operates the network that authorises, clears and settles transactions between issuing banks, acquirers and merchants in more than two hundred countries. Headquartered in Purchase, New York, the company has built a large services business alongside the core network, covering fraud and identity products through its Ethoca and RiskRecon acquisitions, open banking, consulting and loyalty programmes.

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

Manager, Software EngineeringMastercard's Decision Management Platform transforms billions of transactional events into trusted data products, analytics, and decision intelligence that power fraud prevention, identity solutions, operational insights, and business growth.

We are seeking a Manager, Software Engineering to lead a team responsible for building scalable data products and analytics capabilities that enable real-time and batch decision-making across Mastercard. This leader will drive engineering excellence, develop talent, and ensure data is delivered through the right access patterns and fit-for-purpose solutions that maximize value for consumers.

The ideal candidate combines strong people leadership with a passion for data platforms, modern engineering practices, and partnering with business and technology stakeholders to solve complex problems at enterprise scale.

WHAT YOU'LL DO

Lead and Develop High-Performing Teams

* Build, coach, and mentor a team of software and data engineers.

* Foster a culture of accountability, collaboration, innovation, and continuous improvement.

* Support career growth through regular coaching, feedback, and development planning.

Build and Scale Data Products

* Lead the design, delivery, and lifecycle management of data products supporting analytics, AI/ML, reporting, and operational decisioning.

* Partner with stakeholders to understand business needs and translate them into scalable, reusable, and trusted data solutions.

* Drive a product mindset focused on data quality, usability, ownership, and measurable business outcomes.

Enable Fit-for-Purpose Data Consumption

* Ensure appropriate data access patterns are defined and implemented, including real-time streaming, APIs, self-service analytics, curated datasets, and batch processing.

* Guide teams in delivering solutions optimized for scalability, performance, reliability, and long-term sustainability.

* Enable consumers to access trusted data efficiently while maintaining governance and platform standards.

Deliver Strategic Platform Initiatives

* Lead delivery of large-scale data engineering, analytics, and platform modernization initiatives.

* Partner across Product, Architecture, Data Science, and Engineering teams to align technical execution with business priorities.

* Drive planning, prioritization, risk management, and successful delivery of roadmap commitments.

Champion Operational Excellence

* Ensure platform reliability, resiliency, security, and compliance.

* Lead continuous improvement efforts through automation, observability, and operational best practices.

* Drive measurable improvements in platform health, data quality, and engineering productivity.

QUALIFICATIONS:

Required

* Experience leading software engineering, data engineering, or platform engineering teams.

* Strong background building scalable distributed systems, data platforms, or cloud-native solutions.

* Experience delivering complex initiatives in Agile environments.

* Proven ability to influence stakeholders and drive outcomes across multiple teams.

* Strong communication, leadership, and organizational skills.

Preferred

* Experience with data product development, analytics platforms, or decision intelligence solutions.

* Experience with streaming technologies, event-driven architectures, and large-scale data processing.

* Knowledge of cloud platforms, AI/ML enablement, and modern data engineering practices.

* Experience working in payments, fintech, risk, fraud, or financial services environments.

WHAT SUCCESS LOOKS LIKE

* Build and grow a high-performing engineering team.

* Deliver trusted, scalable data products that accelerate business insights and decision-making.

* Establish effective data access and consumption patterns across the enterprise.

* Improve platform reliability, operational efficiency, and engineering velocity.

* Enable faster time-to-value through reusable, governed, and self-service data capabilities.

* Shape the future of Mastercard's Decision Insights platform through innovation and technical leadership.

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.

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