Mastercard
Toronto, Canada (Ethoca)
+ 4 other locations
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.
Manager, Software Engineering
Overview
We are seeking a hands-on Manager, Software Engineering to lead the development of scalable data platforms, backend systems, and data pipelines supporting Mastercard's Portfolio Intelligence products. This role will initially focus on leading a team of Data Engineering contractors while providing strong technical leadership across architecture, delivery, and engineering excellence.
The ideal candidate is a recent practitioner who has built and operated modern data platforms and backend services, can confidently review architecture proposals and code, and leverages AI-powered engineering tools to improve productivity, quality, and delivery speed. As the team evolves, this leader will play a key role in building and developing a high-performing organization of full-time engineers.
What You'll Do
Technical Leadership
Provide technical leadership for backend services, data pipelines, and platform capabilities that support analytics, reporting, and AI-driven products.
Review architecture and design documents to ensure solutions are scalable, maintainable, secure, and aligned with long-term platform strategy.
Conduct and oversee code reviews, promoting engineering best practices, reliability, security, and operational excellence.
Partner with architects, product managers, and engineering leaders to shape technical roadmaps and investment priorities.
Drive adoption of modern engineering practices, including automation, observability, testing, CI/CD, and infrastructure-as-code.
Champion the effective use of AI-assisted development tools to improve developer productivity, code quality, documentation, and delivery velocity.
Team Leadership
Lead and coordinate a team of Data Engineering contractors, establishing clear expectations, accountability, and delivery outcomes.
Manage contractor onboarding, work planning, quality management, and performance oversight.
Foster a culture of ownership, collaboration, continuous improvement, and technical excellence.
Help build the long-term team structure and transition toward a blended organization of full-time and contingent engineers.
Delivery & Execution
Partner with Product and Program teams to translate business objectives into actionable engineering plans.
Ensure predictable delivery of complex initiatives while balancing technical debt, platform investments, and feature development.
Drive technical risk identification, mitigation planning, and execution tracking.
Measure and improve key engineering metrics related to reliability, quality, operational health, and delivery effectiveness.
Qualifications
Required Experience
8+ years of software engineering experience with recent hands-on experience designing and building production systems.
2+ years of engineering leadership, technical lead, or people leadership experience.
Experience leading or managing contractor and/or distributed engineering teams.
Strong experience building backend platforms, APIs, and data-intensive applications.
Experience designing and implementing scalable data pipelines and data processing solutions.
Experience reviewing architecture documents, technical designs, and production-quality code.
Experience working in Agile product development environments.
Experience collaborating with teams in different time zones.
Technical Skills
Strong programming experience in Java, Python, Scala, or similar languages.
Experience with distributed data processing technologies such as Spark.
Experience with modern data platforms such as Snowflake, Databricks, Hadoop, or equivalent.
Experience designing RESTful APIs, microservices, and cloud-native applications.
Solid understanding of data modeling, database design, and data architecture principles.
Experience with CI/CD pipelines, version control, automated testing, and DevOps practices.
Experience with cloud platforms such as AWS, Azure, or GCP.
Preferred Qualifications
Experience building platforms that support advanced analytics, machine learning, or AI use cases.
Experience defining engineering standards and governance practices.
Experience modernizing legacy data platforms and migrating workloads to cloud environments.
Experience implementing AI-assisted software development workflows using tools such as GitHub Copilot, Claude, ChatGPT, or similar technologies.
Success Profile
The successful candidate will:
Earn credibility through strong technical depth and sound engineering judgment.
Effectively lead contractor teams and drive accountability without relying solely on formal reporting structures.
Improve engineering velocity through automation, AI-assisted development, and modern delivery practices.
Balance short-term business commitments with long-term platform investments.
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: