Senior Data Engineer - International Marketing Technology (Seattle, Washington)

This job is with lululemon, an inclusive employer and a member of myGwork – the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly.

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 lululemon Global Marketing Technology Team oversees the technical aspects of lululemon's international marketing technology stack. We aim to provide world class shopping experiences for our guests by enabling data to effectively personalize communication to guests. We are looking for a passionate, high-energy individual who is excited about delivering data-driven capabilities to meet lululemon's growing marketing, insights, analytics, and intelligence capabilities leveraging the best-in-class industry proven solutions. This individual must have a track record of working in a collaborative environment, managing multiple stakeholders in a fast-paced environment and should take pride in evolving the entire organization to create the future data technology platform for growth.

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.

Select responsibilities include:

• 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
• Experience with Azure Cloud, Azure Databricks, Snowflake for data pipeline creation.
• Experience in data pipeline modernization and migration via Databricks Delta Live Tables (DLT) and Unity Catalog

Must haves:

• Acknowledges the presence of choice in every moment and takes personal responsibility for their life.
• Possesses an entrepreneurial spirit and continuously innovates to achieve great results.
• Communicates with honesty and kindness and creates the space for others to do the same.
• Leads with courage, knowing the possibility of greatness is bigger than the fear of failure.
• Fosters connection by putting people first and building trusting relationships.
• Integrates fun and joy as a way of being and working, aka doesn't take themselves too seriously.