Data Engineer
Location: India
Who we are:
Founded in 1998 at Vancouver, lululemon is a performance and lifestyle product company that create transformational products and experiences that build meaningful connections, unlocking greater possibility and wellbeing for all. We are driven by our brand purpose to elevate human potential by making individuals feel their best which helps us design our products with high filter and high style. We use a unique product creation methodology called Science of Feel in all our products to offer convenient, comfortable, and long-lasting experience. We owe our success to our innovative products, commitment to our people, and the incredible connections we make in every community we're in.
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 Bachelors 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. PostgreSQL, MySQL), NoSQL databases (e.g., MongoDB, 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 & SnowPipe.
- Create interactive dashboards and reports inPower BIto 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 PostgreSQL
- 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