Manager Software Engineering (QA/Automation)

About the role

Mastercard is seeking a Manager of Software Engineering focused on QA and automation to lead a high‑performing team delivering enterprise integration solutions on cloud platforms. You will provide technical leadership, drive large‑scale initiatives, and ensure secure, scalable, and high‑quality software delivery aligned with business priorities.

Key responsibilities

• Lead, coach, and develop a high‑performing engineering team, fostering a culture of quality, innovation, and accountability.
• Drive end‑to‑end delivery of complex integration and full‑stack engineering initiatives.
• Manage configuration and integration of cloud‑based applications across the enterprise.
• Provide technical leadership in architecture (microservices, APIs, scalable design) and system design decisions.
• Oversee project execution, balancing scope, timeline, and quality.
• Ensure adherence to enterprise standards, including secure coding, testing, and operational best practices.
• Review and approve technical designs, code, and configurations.
• Partner with stakeholders to translate business needs into technical solutions.
• Drive quality through strong testing strategy, automation, code reviews, and performance validation.
• Implement process improvements to enhance efficiency, automation, and reliability.

Required profile

• Proven experience leading and mentoring software engineering teams.
• Track record delivering large, complex technical solutions.
• Strong troubleshooting and problem‑solving abilities.
• Ability to design systems with operability, monitoring, and reliability in mind.

Required skills

• Core Java development.
• Microservices architecture and API design.
• Test automation frameworks and modern automated testing practices.
• Test strategy definition, coverage planning, and quality metrics.
• Automation architecture design, scalability, and maintainability.
• End‑to‑end testing lifecycle management (planning, execution, defect management, release validation).
• Exposure to AI concepts or tools applied to software testing.
• Secure coding practices and code quality standards.
• Performance engineering and monitoring.