Technology Director, Enterprise Data Platform

Location:

United States of America

State/Province/City:
Washington

City:
Seattle

Business Unit:
Store Support Centre (SSC)

Time Type:
Full-time

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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  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 a Director, Enterprise Data Platforms, you are accountable for the design, delivery, and continuous operation of the enterprise data platform that supports data and analytics across the organization. You will create the enterprise data architecture blueprint and lead the build of the enterprise data platform to enable data discovery and aggregation, and downstream consumption into systems, reports, analytics, and AI workloads.

You will drive operational excellence focusing on availability, observability, security and access controls, reliability, and performance.

You will enable business outcomes by delivering standardized, reusable platform services that support data product and analytics teams, while driving improvements in platform efficiency, scalability, and self-service capabilities. You work in close partnership with the architecture, data governance, insights, analytics, and AI teams, and with business stakeholders to ensure alignment of the platform build with enterprise standards and evolving business needs.

Select responsibilities include:

* Deliver and operate enterprise data platform capabilities

* Own the execution, delivery, and operation of core enterprise data platforms, including data lakes, warehouses, ingestion, and transformation

* Ensure platform reliability, scalability, performance, and security to meet enterprise standards and SLAs

* Drive adoption of self-service data capabilities that enable internal data consumers

* Enable data integration and accessibility

* Lead development of robust data integration capabilities including batch and real-time pipelines (ETL/ELT, streaming, APIs, CDC)

* Provide standardized, reusable frameworks to simplify data ingestion, processing, and access across the organization

* Enable timely and high-quality data delivery for business-critical use cases; enable teams to discover, aggregate and consume data for analytics and AI use-cases

* Drive data governance, quality, and compliance

* Partner with data governance and security teams to ensure adherence to enterprise data policies, standards, and regulatory requirements for data access

* Embed data quality, lineage, and observability practices within platform capabilities

* Promote trusted, well-governed data assets across the organization

* Optimize platform engineering practices

* Lead adoption of modern data engineering tools, technologies, and best practices (e.g.,…