Requirements
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 Princi pal Software Engineer, you will own the system design and implementation of lululemon’s enterprise data & AI 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 and AI infrastructure and reusable components that enable multiple product teams and business domains to build, publish and consume data products. You will build a context and semantic layer infrastructure t hat 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
- 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
- Be accountable for their reliability, cost efficiency and adoption
- Design and build foundational platform components that other engineering teams build on top of, across areas like ingestion, transformation, orchestration, compute and consumption
- Build platform components for ML/AI applications such as point-in-time correct training data, online and offline feature parity or backfilling features at scale
- Architect robust multi-tenant platform standards by establishing clear cross-layer contracts, tenant isolation, and SLOs to enable autonomous producers and consumers, while driving compute and storage efficiency across workloads
- Lead cross team technical initiatives and architecture reviews, influence platform strategy with senior stakeholders and act as a technical mentor and multiplier for Senior engineers
- Write high-quality production code to solve the complex technical challenges when hands-on expertise is required
- 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
- Experience building and governing shared data APIs and platform services ( gRPC /REST APIs, SDKs, CLIs, and simple UIs) enabling consistent, scalable downstream consumption across analytics, AI/ML, and operational use cases
- Experience designing both batch and streaming architectures and clear judgement on when each is the right answer
- Deep understanding of big data and distributed systems challenges including partitioning, shuffle behaviour, skew, idempotency and backfills
- Expertise in configuration management with a framework such as Kubernetes, Helm, Terraform etc.
- Expertise in managing distributed and autoscaled applications in Kubernetes clusters
- Proven experience owning enterprise data lake architecture end-to-end, including ingestion frameworks, pipeline orchestration, DataOps disciplines (CI/CD, SLAs, observability), platform reliability, and security, privacy, and access control in partnership with risk and compliance teams
- 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
- Experience defining enterprise semantic layers and canonical models - including taxonomies, ontologies, and knowledge graphs - used across multiple product teams and business domains
- Exposure to AI-driven systems including optimization, predictions, and Agents; experience working with knowledge representation for LLM-powered applications
- Experience building knowledge bases or data platforms in retail or similarly complex consumer domains
must haves
- Acknowledge the presence of choice in every moment and take personal responsibility for your life.
- Possess an entrepreneurial spirit and continuously innovate to achieve great results.
- Communicate with honesty and kindness and create the space for others to do the same.
- Lead with courage, knowing the possibility of greatness is bigger than the fear of failure.
- Foster connection by putting people first and building trusting relationships.
- Integrate fun and joy as a way of being and working, aka doesn’t take yourself too seriously.
Additional Notes
Authorization to work in Canada is required for this role.
Compensation And Benefits Package
lululemon’s compensation offerings are grounded in a pay-for-performance philosophy that recognizes exceptional individual and team performance. The typical hiring range for this position is from
$196,600 - $258,100 annually; the base pay offered is based on market location and may vary depending on job-related knowledge, skills, experience, and internal equity. As part of our total rewards offering, permanent employees in this position may be eligible for our competitive annual bonus program and equity offerings, subject to program eligibility requirements.
At Lululemon, Investing In Our People Is a Top Priority. We Believe That When Life Works, Work Works. We Strive To Be The Place Where Inclusive Leaders Come To Develop And Enable All To Be Well. Recognizing Our Teams For Their Performance And Dedication, Other Components Of Our Total Rewards Offerings Include Support Of Career Development, Wellbeing, And Personal Growth
- Extended health and dental benefits, and mental health plans
- Paid time off
- Savings and retirement plan matching
- Generous employee discount
- Fitness & yoga classes
- Parenthood top-up
- Extensive catalog of development course offerings
- People networks, mentorship programs, and leadership series (to name a few)
Note: The incentive programs, benefits, and perks have certain eligibility requirements. The Company reserves the right to alter these incentive programs, benefits, and perks in whole or in part at any time without advance notice.
workplace arrangement
Hybrid : In-person collaboration and connection is important to our culture. Work is performed onsite, minimum 4 days per week.
