Engineer I - Data Engineering [T500-21053]

Job Description

About lululemon: 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 products, 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. As we continue to elevate our shopping experience, our India Tech Hub plays a key role in expanding our technology capabilities in Product Systems, Merchandising and Planning, Digital Presence, distribution and logistics, and corporate systems. Our team in India works as an extension of the global team on projects of strategic importance. Engineer I ? Data Engineering About this team: This role is for the lululemon technology organization. lululemon Retail Tech Data & Analytics Engineering is dedicated to building secure, reliable, and performant data roducts 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 lululemon?s business goals. Core Responsibilities: As an Engineer I , 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 degree or diploma (or equivalent experience)?in Computer Science, Software Engineering or Software Architecture preferred; candidates with substantial and relevant industry experience are also eligible? 5 ? 8 years of engineering experience required (E1) 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. Hands on 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. Develop and maintain basic Python / Bash / Shell / any scripting scripts for data manipulation, automation, and integration with analytics workflows Familiarity on Kafka messaging queues and ingestion pipelines Nice to have: Microsoft Fabric by designing data solutions aligned with unified analytics and governance best practices. Nice to have: Knowledge of AI Tools Landscape, Machine learning & Data Science Methodologies