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Lululemon

Direct-to-consumer premium activewear and footwear

Principal Software Engineer - Data and AI Platforms

Data EngineeringConfirmed live in the last 24 hours
Full-timeSeattle, WA, USA

About the Job

Requirements

  • A bachelor’s degree in Computer Science, Information Systems, Information Technology, or equivalent experience is required; a master’s degree is preferred.
  • 11–15 years of progressive software engineering experience with 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 and a track record of writing production code to solve critical and complex technical challenges across multiple languages and frameworks.
  • Experience building and governing shared data APIs and platform services, including gRPC and REST APIs, SDKs, CLIs, and simple UIs, for consistent and scalable consumption across analytics, AI/ML, and operational use cases.
  • Experience designing both batch and streaming architectures and sound judgment about when each is appropriate.
  • Deep understanding of big data and distributed systems challenges, including partitioning, shuffle behavior, skew, idempotency, and backfills.
  • Expertise in configuration management frameworks such as Kubernetes, Helm, or Terraform.
  • 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 such as CI/CD, SLAs, and 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 and making technical trade-off decisions that balance immediate delivery needs with long-term scalability and organizational impact.
  • Experience defining implementation plans and execution approaches for complex, cross-organizational technology programs, and familiarity collaborating with architects to translate architectural designs into actionable engineering roadmaps.
  • Recognized engineering implementation depth and breadth to assess system-wide implications, with the ability to judge when to engage directly with engineers versus delegate.
  • 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.
  • Applicants must be authorized to work for any employer in the United States; employment visa sponsorship is not available.
  • Availability outside standard business hours, including on-call support, may be required based on business needs.

Responsibilities

  • Own the system design and implementation of the enterprise data and AI platform and systems that deliver data products and services for business insights and AI use cases.
  • Ensure data pipelines and services supporting analytics and AI/ML are reliable, efficient, governed, and support operational consumption at scale.
  • Design and build enterprise-grade data and AI infrastructure and reusable components that enable product teams and business domains to build, publish, and consume data products.
  • Build context and semantic-layer infrastructure for insights and AI use cases, and influence delivery of data insights and analytics across multiple use cases.
  • Establish direction and system design for the enterprise data platform, set engineering standards and platform practices across the domain, and serve as the technical authority on the platform.
  • Partner with product, business, and technology stakeholders, including VP-level leadership, on technical strategy, platform roadmap, and cross-functional initiatives.
  • Define the vision and approach for enterprise data initiatives and deliver the technology solution design.
  • Collaborate with architects on enterprise data platform architecture and system design, providing technical expertise on implementation approaches, feasibility, and operational implications.
  • Be accountable for platform reliability, cost efficiency, and adoption.
  • Design and build foundational platform components for other engineering teams across ingestion, transformation, orchestration, compute, and consumption.
  • Build platform components for ML/AI applications, including point-in-time-correct training data, online/offline feature parity, and large-scale feature backfills.
  • Architect multi-tenant platform standards by establishing cross-layer contracts, tenant isolation, and SLOs for autonomous producers and consumers, while driving compute and storage efficiency.
  • Lead cross-team technical initiatives and architecture reviews, influence platform strategy with senior stakeholders, and mentor senior engineers.
  • Write high-quality production code to solve complex technical challenges when hands-on expertise is needed.
  • Identify limitations in current systems and propose technical solutions to improve architecture decisions.
  • Provide executive-level technical advice on implementation challenges, technology recommendations, build-versus-buy decisions, technology selection, and implementation risk.
  • Drive engineering practices and technical workflows adopted company-wide, shaping how the organization builds and operates technology and increasing engineering throughput.
  • Improve engineering velocity and throughput across teams through process optimization, tooling enhancements, and removal of systemic blockers.

About the Company

Lululemon

Direct-to-consumer premium activewear and footwear

Lululemon Athletica focuses on premium activewear, loungewear, and footwear for people with active lifestyles. The company sells high-quality, stylish apparel online and through its own stores, using a direct-to-consumer model and a strong community approach through events and an Ambassador program. Its products are designed for activities like yoga, running, training, and everyday wear, emphasizing performance fabrics, comfort, and versatility. Lululemon differentiates itself from competitors with a premium positioning, a loyal customer base, and a robust community and brand-building strategy, rather than relying on third-party retailers. The company’s goal is to be a leading premium brand in the activewear market by delivering high-quality products, fostering customer loyalty, and growing its direct-to-consumer footprint.

Company size
10,001+
Company stage
IPO
Headquarters
Vancouver, Canada
Founded
1998

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