Engineer II - Data Engineering

Engineer II

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:

lululemon Engineering is dedicated to building secure, reliable, and performant products for our guests and partners. We embrace the philosophies of Agile, DevOps, and SRE to accelerate our development process and provide the most enjoyable, inclusive, and supportive work environment possible. We believe our journey is more fun when it is collaborative, as we focus on the future instead of the past. As an Engineer, you will work as part of a global team supported by our business and architecture partners to help us collaboratively develop and deliver industry leading technology solutions that drive lululemons business goals.

Core Responsibilities:

As an Engineer II, you will help form the core of our engineering practice at lululemon by contributing to all areas of development and operations (pre-production to production). You will be supported by a strong engineering group and established engineering practices. You will be part of a production release team and may perform on-call support functions as needed. Having a DevOps mindset is the key to success in this role, as Engineers are commonly part of full DevOps teams that own all parts of software development, release pipelines, production monitoring, security and support.

• Take part in Agile ceremonies
• Perform engineering assignments using existing procedures and best practices
• Conduct research to aid in product troubleshooting and optimization efforts
• Work closely with global teams to ensure deliver effective technical solutions
• Provide an escalation point and participate in on-call support rotations
• Actively monitor key metrics and report on trends
• Participate in our Engineering Community of Practice
• Contribute to engineering automation, management or development of production level systems
• Perform reliability monitoring and support as needed to ensure products meet guest expectations

Qualifications:

• Completed bachelor's degreeor diploma (or equivalent experience)inComputerScience, Software Engineering or Software Architecture preferred; candidates with substantial and relevant industry experience are also eligible
• 7 9 years of engineering experience required for Engineer II
• Ability to learn, understand, and work quickly with new emerging technologies, methodologies, and solutions in the Cloud/IT technology space
• Hands on experience Snowflake and Medallion architecture along with best practices
• Good knowledge and working experience in Agile methodology and familiar with tools like Jira and Confluence
• Design, develop, and optimize scalable cloud data warehouses in Snowflake , leveraging advanced SQL and performance tuning for analytics.
• Write, optimize, and maintain complex SQL queries, stored procedures, and views for efficient data extraction, transformation, and analysis.
• Handson experience in developing Dynamic Tables and query optimization processes
• Understanding of ETL/ELT workflows using Azure Data Factory (ADF) to integrate diverse data sources into centralized repositories.
• Nice to have: Microsoft Fabric by designing data solutions aligned with unified analytics and governance best practices.
• Nice to have an experience on establishing data governance frameworks leveraging collibra (Data quality tool).
• Nice to have : knowledge on Spark framework (Databricks or any other compute framework tool)
• Nice to have: Knowledge of AI Tools Landscape, Machine learning & Data Science Methodologies