Senior Manager - Data Semantics and Context Modeling (Seattle, Washington)

This job is with lululemon, an inclusive employer and a member of myGwork – the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly.

Description & Requirements

who we are

lululemon is an innovative performance apparel company for yoga, running, training, and other athletic pursuits. Setting the bar in technical fabrics and functional design, we create transformational products and experiences that support people in moving, growing, connecting, and being well. We owe our success to our innovative product, emphasis on stores, commitment to our people, and the incredible connections we make in every community we're in. As a company, we focus on creating positive change to build a healthier, thriving future. In particular, that includes creating an equitable, inclusive and growth-focused environment for our people.

about this team

The Enterprise Data & AI organization is a strategic and operational driver of growth for lululemon, owning and building the data and AI platforms and services that enable the enterprise to operate with intelligence at scale. The team leads the design and delivery of a trusted unified data foundation, AI-driven data analytics and insights, and AI solutions across lululemon's vertically integrated retail ecosystem, while embedding strong data governance and responsible AI practices from the very beginning. By applying AI to critical business challenges and creating new, transformative AI solutions, the team helps reshape how lululemon operates. Through deep partnership with product, technology, and business teams, Enterprise Data & AI accelerates product innovation, unlocks measurable value, elevates guest and educator experiences, and drives enterprise efficiency.

core responsibilities

The Enterprise Data & AI team is at the center of how lululemon scales as a data-driven organization. As the Senior Manager, Data Semantics and Context Modeling, you will lead the design, governance, and adoption of a trusted semantic layer across our enterprise data platform. In this role, you'll help shape how the business ontology, context, and knowledge are represented in the Enterprise Data Platform. You will build and provide the models and semantic abstractions that support context-driven analytics, BI, and AI/ML solutions. You will integrate semantics with the data catalog, metadata, and lineage tooling to create discoverability. You will create representations such as knowledge graphs to capture relationships, attributes and semantics of lululemon's enterprise data, enabling the right context to be integrated into downstream AI applications and insights generation.

If you're motivated by solving complex alignment challenges, influencing at scale, and building something foundational that impacts the entire organization, this is a rare opportunity to define how data and AI work at lululemon.

Select Responsibilities Include:

• Own and evolve the enterprise semantic layer, ensuring consistent definitions, metrics, and meaning across all consumption patterns.
• Provide dimensional models and semantic abstractions that contextualize and improve the performance of analytics, BI, AI/ML, and other downstream applications.
• With a use-case based lens, identify and implement generative AI and multimodal methods to create the semantic layer and provide appropriate context for downstream analytics and AI use-cases.
• Maintain the business context layer, including hierarchies, relationships, business rules, and event semantics.
• Integrate semantics seamlessly with the data catalog, metadata, and lineage tooling to enable discoverability and trust.
• Drive adoption of the semantic layer across BI tools, dashboards, ad hoc analysis, data products, and AI-enabled analytics experiences.
• Partner with the enterprise data platform, and the data and insights delivery teams to enable delivery of context-driven data insights.
• Define and maintain canonical enterprise data models and common business entities (e.g., customer/guest, product, store, transaction, inventory).
• Lead and develop a high-performing team of data and semantic modeling experts
• Foster a culture of collaboration, accountability, and continuous improvement

Qualifications

• 10+ years in data, analytics, or information architecture, with deep experience in data semantics and taxonomy
• Experience building or managing a centralized semantic layer or metrics platform, data mesh, and data products
• 3+ years in senior leadership managing teams with deep complexity or multiple projects
• Strong understanding of:
  • Semantic layers and context modeling
  • Business metrics and KPI frameworks
  • Data governance and stewardship models