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 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.
Data Engineer II
Location: India
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.
Successful delivery of data projects meeting business requirements and data quality standards
Technical implementation quality for complex data pipelines ensuring scalability and performance within established data architecture
Data quality across assigned work including data validation, testing, and documentation
Mentorship of junior data engineers including code review feedback with measurable skill improvement
Alignment of data solutions with business analytics objectives and stakeholder satisfaction
Document data architecture, pipeline designs, and technical specifications for data systems
Participate in on-call rotation including incident response, troubleshooting data issues, and conducting post-mortems
Collaborate with analytics teams and business stakeholders on data requirements, technical feasibility, effort estimation, and scope definition
Conduct thorough code reviews ensuring adherence to data standards and identifying data quality issues
Optimize performance of queries, data pipelines, and storage through testing, profiling data processing, and implementing improvements within architectural constraints
Apply Agentic AI concepts to improve intelligent automation, decision-making and adaptive system behaviors
Are a main contributor in Agile ceremonies
Work closely with global teams to ensure deliver effective technical solutions
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
7 to 9+ years of engineering experience
Design and develop data pipelines that extract, transform, and load data from multiple sources into data warehouses and lakes.
Design data models, schemas, and data storage solutions including relational databases (e.g. Postgre SQL, My SQL), No SQL databases (e.g., Mongo DB, Cassandra), and cloud-based data warehouses (e.g., Snowflake, Redshift).
Build scalable ETL/ELT processes using tools and languages such as SQL, Python, Spark, and cloud platforms (e.g., AWS Glue, Azure Data Factory, Airflow) ensuring data quality, reliability, and performance for analytics and business intelligence.
Working experience in Snowflake - data modelling, ELT using Snowflake SQL, deploying Snowflake features such as data sharing & Snow Pipe.
Create interactive dashboards and reports in Power BI to deliver actionable business insights.
Should have hands on experience in Power BI features including but not limited to DAX, Power query, Power map.
Fluency with relational databases especially Postgre SQL
Independently write high-quality, scalable data transformation code (e.g., SQL, Java, Python) and work with data pipeline platforms (e.g., Kafka, Spark) following data engineering best practices
Lead technical design discussions on data pipeline implementation approaches presenting proposals and facilitating team alignment
Experience with Data Warehousing and Snowflake. Knowledge of using snowflake objects for Power Bi data source would be preferred.
Demonstrated familiarity with AI/ML data lifecycle concepts, including feature engineering, model inference pipelines, data drift considerations, and production monitoring.
Good to have Hands-on experience supporting AI-driven and agent-based systems by building and operating robust data pipelines, ensuring feature readiness, and providing reliable operational data to enable intelligent automation and data-driven decision-making.
Strong hands-on experience with designing and implementing CI/CD workflows
Experience working with job schedulers like Airflow
Ability to learn, understand, and work quickly with new emerging technologies, methodologies, and solutions in the Cloud/IT technology space
Excellent pull request review skills and attention to detail
Good knowledge and working experience in Agile methodology and familiar with tools like Jira and Confluence
Good to have strong knowledge and experience with infrastructure provisioning tools like Terraform and workflow orchestration tools like Airflow
Experience in mentoring junior developers and providing technical leadership
Excellent pull request review skills and attention to detail
Industry experience in Retail domain is a plus
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