Principal Software Engineer - Data and AI Platforms (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. 

Our data and AI platform foundation is built on enterprise data lake architecture, standardized ingestion and integration frameworks, and canonical semantic models spanning product, customer, and supply chain domains.

The platform advances data insights and AI capabilities while maintaining rigorous data governance, observability, and platform reliability. The team delivers self-service data capabilities and shared platform services that enable consistent, trustworthy consumption across analytics, AI/ML, and operational use cases at enterprise scale.

core responsibilities

As a Principal Software Engineer, you will own the system design and implementation of lululemon's enterprise data platform and the systems that ensure delivery of data products and services that power high-impact business data-driven insights and AI use cases. You will ensure data pipelines and services that enable analytics, AI/ML, are reliable, efficient, and governed, and support operational consumption at scale.

You will design and build enterprise-grade data products that serve as the data foundation across multiple product teams and business domains. You will build a context and semantic layer and enterprise data model that enables insights and AI use-cases. You will enable and influence the engineering delivery of data insights and analytics across multiple use-cases.

You will establish the direction and system design for the enterprise data platform, set engineering standards and platform practices adopted across the domain, and serve as the definitive technical authority on the enterprise data platform. You will partner closely with product, business, and technology stakeholders including VP-level leadership, on technical strategy, platform roadmap, and cross-functional initiatives.

This role may require availability outside of standard business hours, including on-call support, based on business needs.

select responsibilities include:

• Define vision and approach for enterprise data initiatives and effectively and efficiently deliver the technology solution design
• Demonstrate expert-level functional coding proficiency, writing high-quality production code to solve the complex technical challenges when hands-on expertise is required
• Collaborate closely with architects on enterprise data platform technical architecture and system design, and provide deep technical expertise on implementation approaches, feasibility assessment, and operational implications
• Challenge and improve existing architecture decisions by identifying limitations in current systems and proposing technical solutions based on system design expertise

• Provide executive-level technical advisory on complex implementation challenges and technology recommendations focused on build vs. buy decisions, technology selection, and implementation risk assessment
• Drive engineering practices and technical workflows adopted company-wide, shaping how the organization builds and operates technology and increasing engineering throughput
• Drive engineering velocity and throughput improvements across multiple teams through process optimization, tooling enhancements, and removal of systemic blockers

qualifications

• Bachelor's degree in Computer Science, Information Systems, Information Technology, or equivalent experience; Master's preferred

• 11-15 years of progressive software engineering experience with demonstrated expertise in large-scale system design, technical architecture, and cross-functional leadership related to data systems and platforms or equivalent technology domains

• Expert-level coding ability with a track record of writing production code to solve the most critical and complex technical challenges across multiple languages and frameworks

• Deep experience analyzing complex system interactions to identify optimal solution approaches; proven ability to make technical trade-off decisions balancing immediate delivery needs with long-term scalability and organizational impact

• Experience defining implementation plans and execution approaches for complex, cross-organizational technology programs; familiarity collaborating with architects to translate architectural designs into actionable engineering roadmaps

• Recognized depth in engineering implementations, combined with breadth to assess system-wide implications; proven ability to make rapid, high-confidence judgements on when to engage directly with engineers versus delegating

• Demonstrated ability to influence product strategy and investment decisions through technical insights on feasibility, risk, and business impact