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.

As a Senior Data Engineer, you will lead the design and implementation of complex data systems and pipelines spanning multiple data sources and destinations, establishing technical direction for the data domain including data quality standards, pipeline patterns. Focusing on data quality and system performance, and establish data engineering standards adopted across the domain, data modelling, Observability and alerting mechanism in cloud (Azure/AWS). Write exemplary data transformation code demonstrating data engineering best practices in critical systems as technical reference for teams.
Designing, Building and maintaining scalable ETL data processing systems: creating and maintaining optimal data pipelines architecture.
Identify, design and implement internal process improvements (Automating manual steps, optimizing delivery)
Create data solutions for BI and data science teams.
Establish and enforce data quality standards, pipeline patterns, and data engineering best practices across multiple teams in data domain




Conduct high-impact code reviews focusing on data quality, performance, and long-term maintainability of data systems
Coordinating with cross teams and BAs for requirement analysis.

Deep knowledge of relational databases, cloud data warehouses, and selecting appropriate storage solutions for use cases; experience designing complex data architectures across multiple storage systems.
Experience in Snowflake building data pipelines good to have AI Cortex, Snowflake notebook.
Worked on orchestrator Airflow or Azure Data Factory
Experience designing and optimizing data solutions using Snowflake, including data modeling, performance tuning, workload management, and scalable data product development.
Robust experience implementing modern data engineering patterns, including workflow orchestration, metadata-driven pipelines, CI/CD, and Lakehouse architectures leveraging open table formats such as Apache Iceberg.
Preferred experience in data stacks utilizing: Snowflake, AWS, Azure, GitLab, DBT.
Build test and deploy software solutions in production.
Data Quality standards and data validation.

Bachelor's degree in computer science, Data Science, Engineering, or related technical field, or equivalent experience; master's degree beneficial
~8-12 years of experience building enterprise data solutions, data modelling, building scalable data pipelines (Batch Streaming), experience in Azure /AWS services.

Foster connection by putting people first and building trusting relationships.

Data governance.
Demonstrated ability to establish data quality standards, quality and governance frameworks, and monitoring practices across a domain.
Basic understanding of AI/ML Model registry
Mentoring new team members, demonstrate leadership qualities.

📌 Senior Data Engineer - AI & Data (Bengaluru)
🏢 lululemon
📍 Bengaluru