lululemon
Website:
lululemon.com
Company:
https://www.linkedin.com/company/lululemon
Seniority: Mid-Senior level
Industries: Retail
Job details:
Who we are:
Founded in 1998 at Vancouver, lululemon is a performance and lifestyle product company that create transformational products and experiences that build meaningful connections, unlocking greater possibility and wellbeing for all. We are driven by our brand purpose to elevate human potential by making individuals feel their best which helps us design our products with high filter and high style. We use a unique product creation methodology called Science of Feel in all our products to offer convenient, comfortable, and long-lasting experience. We owe our success to our innovative products, commitment to our people, and the incredible connections we make in every community we're in.
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:
As the Director, Data and Insights Delivery, you are accountable for the end-to-end delivery, implementation, and operation of enterprise data products, and deliver insights that directly lead to measurable business outcomes. This role owns the full lifecycle of enterprise and domain data products — from ingestion and transformation through serving and consumption — ensuring quality, reliability, adoption, and reuse across domains. In this role, you will partner with the data platform team to leverage the enterprise platform and implement and publish data products as single, consistent source of truth. You will use the enterprise catalog and semantic/context layer to deliver insights and create self-service capabilities for analysts and business users and stakeholders. You will partner closely with Product Managers and use-case owners in the business, and the platform, architecture and governance teams to translate business needs into solutions built on the enterprise data platform.
Select responsibilities include:
- Lead end-to-end delivery of prioritized enterprise and domain data products and insights use cases, ensuring all solutions leverage the enterprise data platform services, semantic models, and standard delivery patterns and that reusable assets back are contributed back to the platform
- Partner with Product Managers, technology platform owners, domain and business stakeholders to co-develop use-case roadmaps, delivery priorities, and value-realization milestones; serve as a trusted advisor to the business on serving data-driven insights
- Deliver insights by building standardized interfaces and self-serve capabilities including semantic views, auto-generated insights, and interactive/ conversational experiences enabled by AI.
- Use the semantic layer and business context to drive consistent definitions, KPIS, and metrics in all downstream reporting and analytics, serving consumption across Finance, Product, Merchandising, Supply Chain, Stores, and Enablement functions.
- Define and manage data product SLAs and quality standards, including observability, incident management, and continuous improvement of performance and usability
- Build and lead domain-aligned, multi-disciplinary delivery teams, promoting strong collaboration between business, data, and engineering partners and fostering a culture of accountability, continuous improvement, and strong business partnership
Qualifications:
- Bachelor's degree in computer science, mathematics, software engineering, or related field, Master's degree preferred.
- Demonstrated ability to set enterprise data vision enabling business transformation and data-driven competitive advantage
- Experience defining strategic technical direction for data products and services, leveraging data engineering and AI advancements
- Senior technical leadership experience architecting and delivering enterprise data and analytics engineering solutions to support business outcomes at scale
- Strong background as a software engineer with hands-on experience in native implementation of cloud-based data platforms, data engineering pipelines and enterprise data products and services.
- Experience defining and managing data product SLAs, quality standards, and operational monitoring frameworks at enterprise scale
- Proven ability to partner with business and technology leaders across domains including Finance, Product, Merchandising, Supply Chain, and Operations
- Track record of driving measurable business impact through data delivery — including revenue uplift, cost efficiency, or decision speed improvements
- Strong people leadership and team building capability, with experience building domain-aligned, multi-disciplinary technical/engineering teams
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