Manager, Software Engineering, ITC

About the role

Nike's Data & AI (DAI) team builds scalable, secure and intelligent platforms that support decision-making across the company and tailor experiences for its global community. It is looking for an engineering manager who can nurture high-performing teams in a fast-paced, collaborative setting and has a strong track record of delivering sophisticated data platforms and innovative services.

Key responsibilities

• Guide and inspire a team of software engineers in designing, building and maintaining robust, scalable data platforms and services.
• Lead the architecture and delivery of SDKs, APIs and microservices.
• Work with product managers, architects and other engineering leaders to define technical strategy, set goals and shape the long-term roadmap for data and analytics.
• Build a culture of continuous improvement, creative problem-solving and engineering excellence.
• Champion best practices in software engineering, data governance, operational monitoring and platform observability.
• Align projects with organisational priorities such as digital modernisation, cloud cost efficiency and data governance.
• Develop agentic and AI/LLM-powered enterprise applications.

Required profile

• Minimum of 10 years of software development experience, including distributed systems, cloud-native architecture and modern data platform technologies.
• Bachelor's degree in computer science, software engineering or a related field (master's or PhD preferred).
• At least 3 years of leadership experience managing engineering teams, recruiting talent and mentoring staff.
• Expertise in deploying solutions on at least one major cloud platform (AWS, Azure, GCP or OCI).
• Strong communication skills and stakeholder management, including engagement with senior leadership.

Required skills

• Deep knowledge of AIML technologies, open-source tools and agentic workflows, with the ability to make build-versus-buy decisions.
• Knowledge of data pipeline frameworks, metadata management and data governance controls.
• Architectural design patterns and foundational computer science principles.