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.
