The Role
Reporting directly to VP, Technology GC, the Senior Director, Enterprise Data & AI (ED&AI) GC is a senior leadership role responsible for shaping and executing the enterprise data, analytics, and AI vision across Greater China. This leader will build and scale team to power data-driven decision making, automation, and breakthrough AI-enabled products that support GC's business growth.
In this role, you will:
Define and articulate a compelling enterprise data & AI vision, strategy, and multi-year roadmap in alignment with GC business priorities and our global technology strategy.
Lead and grow teams to build a high-performing and integrated organization.
Partner with the Global and Geography Technology teams to deliver scalable, 'bleeding edge' technology solutions that push the boundaries of what the business can do today and accelerate change in GC.
Evangelize data, analytics, and AI capabilities across the business to drive adoption of data-driven decision making, automation, and AI-powered ways of working.
Drive measurable business outcomes through data, analytics, and AI, accelerating consumer engagement, digital commerce growth, speed of decision-making, and operational efficiency across Greater China.
Lead the annual process of creating, maintaining, and implementing the GC ED & AI Technology Portfolio.
Identify and prioritize high-impact opportunities to leverage AI/ML and analytics to address customer needs and solve complex, high-business-impact problems.
Oversee end-to-end delivery of data platforms and AI/ML products, from ideation and architecture through launch, iteration, and operations.
Elevate engineering excellence through best practices in data architecture, MLOps, security, scalability, uptime, and reliability.
Ensure adherence to data governance, AI ethics, privacy, and regulatory standards in partnership with legal and compliance teams.
Manage cross-functional teams and stakeholders — including product owners, data engineers, ML engineers, and scrum masters — to deliver against a shared backlog.
What You'll Need to Succeed
Experience & Leadership
15+ years in data and analytics engineering, data science, AI/ML, or data product roles, with a proven track record of building and scaling enterprise data & AI capabilities.
Significant experience leading and growing multi-disciplinary technology teams, including people leaders, and providing technical leadership to cross-functional and business teams.
Demonstrated success delivering AI/ML-powered products and enterprise-scale data platforms from strategy through production.
Experience leading AI transformation beyond data science initiatives and agentic workflows to also include leading AI-driven operating model transformation with AIDLC (AI Development Life Cycle).
Technical Expertise
Data or analytics engineering experience with 'big data' technologies and platforms (e.g., Hadoop ecosystem, Spark, Hive).
Knowledge of and experience with cloud technologies (e.g., AWS – EMR, S3, Lambda) and migration of tools/platforms from on-prem to the cloud.
Strong understanding of AI/ML technologies, data pipelines, machine learning frameworks, and modern cloud infrastructure.
Experience with data warehousing, dimensional modeling, ETL development, streaming/event processing (e.g., Kafka, Kinesis), and data visualization/BI tools.
Familiarity with Agile/Scrum product development methodologies and MLOps/DevOps practices.
Leadership & Soft Skills
Exceptional strategic thinking, problem-solving, and the ability to translate business needs into a data & AI roadmap.
Excellent communication and stakeholder-influencing skills, including with senior/executive leadership.
Ability to thrive and lead in a fast-paced, ambiguous, and rapidly evolving environment.
Preferred Qualifications
Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Information Systems, or a related field; MBA a plus.
Experience with AI ethics, privacy, and regulatory considerations, particularly within Greater China.
Knowledge of industry-specific AI applications (e.g., retail, e-commerce, supply chain, etc.).
Experience partnering across global and geography technology organizations in a matrixed environment.
Skills Required
- 15+ years of experience in data and analytics engineering, data science, AI/ML, or data product roles
- Proven experience building and scaling enterprise data and AI capabilities
- Significant experience leading multidisciplinary technology teams, including people leaders
- Experience delivering AI/ML-powered products and enterprise-scale data platforms from strategy through production
- Experience leading AI transformation, agentic workflows, and AI-driven operating model transformation using AIDLC
- Experience with big data technologies and platforms such as Hadoop, Spark, and Hive
- Knowledge of cloud technologies such as AWS, EMR, S3, and Lambda
- Experience migrating tools and platforms from on-premises environments to the cloud
- Strong understanding of AI/ML technologies, data pipelines, machine learning frameworks, and modern cloud infrastructure
- Experience with data warehousing, dimensional modeling, ETL development, streaming or event processing, and data visualization or BI tools
- Familiarity with Agile/Scrum product development and MLOps/DevOps practices
- Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, Information Systems, or a related field
- Experience with AI ethics, privacy, and regulatory considerations, particularly in Greater China
- Knowledge of industry-specific AI applications, including retail, e-commerce, or supply chain
- Experience partnering across global and geography technology organizations in a matrixed environment
Nike Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Nike and has not been reviewed or approved by Nike.
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Retirement Support — A 401(k) with a company match is complemented by options such as a Mega Backdoor Roth and deferred compensation for eligible earners. Financial coaching and structured savings programs support long-term financial security.
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Equity Value & Accessibility — An Employee Stock Purchase Plan with a stock discount sits alongside broad-based equity vehicles like RSUs and non-qualified stock options. These avenues expand wealth-building opportunities beyond base pay.
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Parental & Family Support — Paid parental leave includes maternity and paternity time, recently expanded in the U.S. to 16 weeks and extended to part-time retail teammates. Additional supports include childcare assistance at select locations and family-building benefits such as fertility, surrogacy, and adoption.
Nike Insights
What We Do
At NIKE, Inc., we innovate to serve athletes*. Every teammate - from coder to creator - plays a role in making these athletes’ dreams real. Our tech, data, and digital teams push limits every day, building the future of sport and the tools that drive it. Here, curiosity is fuel. Innovation is the game plan. Different perspectives keep us on the offense. You’ll solve challenges worth tackling, grow fast and belong to a team that backs you to do the right thing. Bring your drive. Bring your bold. Let’s move the world, together. Take your first step at nike.com/careers * If you have a body, you’re an athlete.
Why Work With Us
At NIKE, Inc., your dedication fuels the future of sport. There is a sense of pride that comes from representing an iconic brand and shaping its future. Here, we treat every day as a new opportunity to push boundaries, ask tough questions and share whole-hearted convictions. We are a team – united by the belief that anything is possible.
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