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
This team delivers Retail and OMNI data products that enable global store reporting and enterprise ‑ wide insights, supporting the business through trusted, scalable, and high ‑ quality data. Operating as a global group, the team owns the full data ecosystem—from ingestion and transformation to warehousing and analytics—covering semantic models, governance, technology operations, and new and emerging AI and data capabilities. Using tools such as Azure Data Factory, Snowflake’s Medallion architecture (Bronze, Silver, and Gold layers), and Power BI, the team partners closely across the enterprise to deliver curated, business ‑ ready data products. Together, the team sets the technical direction for the data domain, making thoughtful decisions around orchestration, data modelling, transformation logic, semantic layer design, and performance optimization, while establishing strong standards for data quality, governance, and observability to ensure reliable insights at scale.
Core responsibilities
As a Senior Data Engineer, you will lead the design and implementation of complex data systems and pipelines spanning multiple data sources and destinations, establishing technical direction for the data domain including data quality standards, pipeline patterns, and governance practices while ensuring solutions meet scalability and reliability requirements. You will make implementation decisions for data domain including data modeling approaches, transformation logic, and optimization strategies, conduct high-impact code reviews focusing on data quality and system performance, and establish data engineering standards adopted across the domain. You will mentor data engineers at multiple levels providing guidance on advanced data concepts and career development, partner with analytics and business stakeholders on data strategy and roadmap planning, and lead resolution of critical data quality issues and pipeline failures.
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Lead implementation of complex data systems and pipelines spanning multiple data sources and destinations within established data architecture frameworks
Write exemplary data transformation code demonstrating data engineering best practices in critical systems as technical reference for teams
Establish and enforce data quality standards, pipeline patterns, and data engineering best practices across multiple teams in data domain
Conduct high-impact code reviews focusing on data quality, performance, and long-term maintainability of data systems
Lead incident response for major data pipeline failures including coordination and post-mortem facilitation
Qualifications
Bachelor’s degree in Computer Science , Data Science, Engineering, or related technical field, or equivalent experience; Master’s degree beneficial
6-10 years of experience building enterprise data solutions and leading data infrastructure initiatives across engineering teams, or equivalent
Proven experience designing data system architectures for a domain balancing data requirements and constraints; track record of driving data pipeline design decisions across multiple teams
Deep knowledge of relational databases, NoSQL databases, cloud data warehouses, and selecting appropriate storage solutions for use cases; experience designing complex data architectures across multiple storage systems
Demonstrated ability to establish data quality standards, quality and governance frameworks, and monitoring practices across a domain
Advanced Power BI expertise(5–7+ years), including enterprise ‑ scale data modelling, DAX, performance optimization, and production deployments
Strong hands ‑ on experience with modern data platforms, including Azure Data Factory (or equivalent orchestration tools) and Snowflake architecture, performance tuning, and Medallion data models
Demonstrated leadership in data governance and quality, establishing monitoring, observability, and data quality frameworks across analytics 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 $132,600 - $174,000 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, 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.
