WHO YOU’LL WORK WITH 

They will collaborate closely with senior leaders across Data, AI, Knowledge, Platform Engineering, Cloud Infrastructure, Security, and Architecture, while partnering with product and engineering teams across Nike Digital, Supply Chain, and Enterprise Technology, as well as external technology partners and vendors driving platform innovation and scale. They will also provide technical leadership to a broad community of principal engineers, architects, and engineering teams across geographies, shaping a culture of engineering excellence through mentorship, technical guidance, and cross-functional influence. 

WHO WE ARE LOOKING FOR 

We are looking for a seasoned technical leader with deep expertise in enterprise data and analytics platforms—someone who combines strong architectural judgment with hands-on experience building and scaling modern data ecosystems in complex, global environments. This individual should be fluent in cloud-based platforms, distributed systems, and modern data components, including batch and streaming pipelines, orchestration, storage, metadata, and observability. A strong foundation in semantic layers, ontology, taxonomy, and knowledge graphs is critical, along with the ability to design platforms that support the full data lifecycle—from ingestion and transformation to governance and self-service access. 

The ideal candidate brings proven experience defining technical direction, simplifying complexity, and establishing scalable architectural patterns, standards, and guardrails that drive consistency, reliability, and long-term maintainability. Beyond technical depth, we are looking for someone who can partner effectively across engineering, product, infrastructure, and security teams, and who leads through influence, mentorship, and credibility to elevate engineering excellence and align platform capabilities with business and developer needs. 

WHAT YOU’LL WORK ON 

You will shape the technical direction of Nike’s enterprise data, analytics, and AI platforms, driving architecture, modernization, and innovation at global scale. You will partner across engineering, product, infrastructure, and security to build resilient, intelligent, and self-service capabilities that accelerate business impact. 

• You will define and advance the long-term technical strategy for enterprise data and AI platforms, with a focus on scalability, resilience, security, and cost efficiency. 

• You will lead platform architecture and modernization across cloud-native data, analytics, and AI capabilities that support global engineering and business teams. 

• You will build platform components that enable Semantic layer, Ontology, Taxonomy and Knowledge graphs. 

• You will establish standards and reference patterns for platform design, governance, observability, automation, and high-quality data operations. 

• You will partner with product, platform, infrastructure, and security leaders to align roadmaps and enable self-service experiences at scale. 

• You will champion innovation in AI, GenAI, automation, and real-time data capabilities to unlock new platform and developer value. 

• You will influence senior stakeholders and mentor engineering leaders to raise the bar on technical excellence, platform outcomes, and organizational capability. 

WHAT YOU BRING 

• Bachelor's degree in computer science or related field. Will accept any suitable combination of education, experience and training.  

• 10+ years software engineering experience as an individual contributor.  

• Proven track record as a Distinguished Engineer or equivalent role in a technology-driven organization.  

• Strong knowledge of data structures, algorithms, and distributed computing.  

• A strong understanding of enterprise data privacy, governance, and access controls, with the ability to design and enforce safeguards that protect sensitive data. 

• Has deep knowledge of Semantic layer, Ontology, Taxonomy and Knowledge graphs 

• Deep understanding of system performance tradeoffs, and engineering for high availability.  

• Strong understanding of AI/ML technologies and their application to data-driven solutions.  

• Excellent leadership and communication skills, with the ability to influence and inspire teams.  

• Proven ability to drive innovation and solve complex technical challenges.  

• Strong analytical and problem-solving skills.  

• Active involvement in the open-source community and a history of contributing to relevant projects and/or experience in publishing technical articles.