Senior Principal Engineer - Product Supply Chain and Corporate Systems

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.

lululemon Global Supply Chain Engineering builds secure, reliable, and scalable platforms that enable the end-to-end lifecycle of our products from concept design through merchandising, sourcing, and supply chain execution. We partner deeply with creative, commercial, and operational teams and embrace modern engineering practices (Agile, Dev Ops, SRE) to deliver systems that scale globally. This role sits at the intersection of Digital Product Creation, Go to Marking (GTM), and enterprise platforms, helping to transform historically manual and sequential workflows into digitally enabled, data‑driven systems.

• Own and evolve the end-to-end Go to Market technical architecture, spanning Product Lifecycle Management, digital asset management, visualization, merchandising, and supply planning systems.
• Partner with Principal Architects, Technology Directors and Executives to define the future-state Go to Market capability roadmap.
• Lead by example as a hands‑on technologist, actively contributing to code reviews, prototyping, and complex debugging across diverse technology stacks.
• Design and implement microservices‑based, distributed systems that are scalable, reliable, and fault‑tolerant.
• Define canonical data models for styles, colorways, BOMs, tech packs, and related product data, and establish clear system-of-record boundaries.
• Architect scalable 2D and 3D digital product creation pipelines, including patterns, materials, garment assets, and rendered outputs.
• Enable centralized digital libraries (blocks, patterns, trims, fabrics) to improve reuse, speed and consistency across seasons.
• Apply AI and automation to the Go to Market workflows such as color‑ups, BOM and tech pack creation, and product recommendations, embedding intelligence directly into enterprise tools and human‑in‑the‑loop controls.
• Replace rigid Go to Market stage gates with progressive readiness states, improving resilience to late changes and decision confidence at critical milestones (ex: Sketch Review, GLF, Buy Sign‑Off)
• Drive modernization of legacy architectures, introducing cloud‑native, event‑driven, and containerized patterns to improve performance and reduce technical debt.
• Serve as a coach and mentor to Principal Engineers and high‑potential technical leaders, building a pipeline of engineering excellenc[e].
• Ability to develop headless system.
• Design API first and event driven integration.
• Create seamless, automated data flows through clean, well‑integrated system interfaces.

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, or equivalent professional experience.
• 15+ years of progressive experience in software engineering.
• Proven experience designing and evolving complex, multi‑system platforms, ideally involving Product Lifecycle Management or Product Lifecycle technologies.
• Strong hands‑on experience with Java and Python, and deep understanding of modern application frameworks (ex: Springboot).
• Familiarity with digital product creation ecosystems (2D/3D tooling, patterns, materials, visualization) and asset management concepts.
• Practical experience applying AI/ML to operational workflows.
• Deep expertise in the following:
• Cloud‑native architectures and services (AWS, Lambda, S3, containerization, Kubernetes)
• Database technologies (relational, No
  
  SQL, vector, time‑series systems and enterprise governance)
• API‑based and event‑driven architectures, including real‑time data integrations (ex: Kafka or equivalent)
• Fam…