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Location: India
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:
Global Sourcing team enables Lululemon's supply chain from raw materials to finished good production through innovative technology solutions. Our purpose is to empower the organization to drive innovation and deliver on its strategic vision that includes cultivating a responsible supply chain through sustainable practices while ensuring a superior product quality and compliance. We are a team that dares to innovate, support each other, elevate our partnerships and collaborate while having fun. 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 lululemon’s business goals.
Core Responsibilities:
As a Data Engineer II, you will design and implement data solutions independently including complex data pipelines, data models, and data infrastructure that enable analytics and insights across the organization while applying data engineering best practices and performance optimization techniques. You will lead technical design discussions on data pipeline architecture and data modeling approaches, conduct thorough code reviews ensuring data quality and maintainability standards, and mentor junior data engineers on data transformation logic, optimization techniques, and troubleshooting approaches. You will collaborate closely with analytics teams, data scientists, and business stakeholders on data requirements and feasibility, make implementation decisions for data pipelines including transformation logic and optimization strategies, and contribute to data engineering standards and practices that improve data quality and pipeline reliability.
Qualifications: