Senior Engineer II - DAIM

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. Senior Engineer II About this team: Data Intelligence Platform team is responsible for housing the enterprise data within Lululemon. The enterprise data helps teams to build intelligent applications, optimized processes, and personalized guest experiences. The team serves as a source of reference for cross functional reporting, marketing, and data science teams. Core Responsibilities: As a Senior Engineer II, you will work as the technical leader for the product(s) your team delivers. You will be counted on as a leader in your technology space, as you contribute to all areas of development and operations (pre-production to production). As a Senior Engineer II, you will dedicate a fair amount of time to the planning and discovery of tools and practices inside your given area of expertise. You will apply that knowledge by working closely with Staff Engineers to promote platform level change. Senior Engineer IIs, take production readiness and performance personally and help drive continuous improvement. You will be part of a day-to-day production release team and may perform on-call support functions as needed. You will be considered the technical owner of the production system(s) you work on and focus on how your product(s) are delivered and how to optimize them for efficiency, security and reliability. Main contributor for product roadmaps and reliability strategy Partner with project management to deliver status and performance updates Conduct research to aid in product development and tools selection Provide an escalation point and participate in on-call support rotations Actively monitor key metrics, reports on trends, and make improvement recommendations Facilitate an Engineering Community of Practice for your product(s) Contribute to engineering automation, management or development of production level systems Review product roadmaps and guide intake acceptance for a set of production systems Own reliability for a defined set of production systems Own the delivery lifecycle for a defined set of production systems Implement appropriate ML algorithms, conducting experiments, register the ML model, and produce prediction or ML Model Serving endpoint Deploy, manage, and optimize machine learning models in multiple environments (re: DEV to QA to PROD), and doing this through automation on Git Repository CICD pipeline to promote the codes data model changes. As a contributing member on Data Intelligence Platform, this individual will be working with Data Engineers Data Scientists ML Developers among multiple federated teams within lululemon. Its important to keep an open and customer-service oriented mindset. Interface with cross functional teams and assist them with their ML or MLOps project. Build code samples or accelerator packages (say sample templates) and share with others. Build robust and scalable pipelines using Snowflake, Databricks Unity Catalog, and orchestration tools such as Azure Data Factory or Airflow Embrace automation, reduce cost, and human dependencies wherever possible. Bring a product development mindset to every aspect of ML engineering or MLOps engineering development activities Qualifications: Bachelors degreeor diploma (or equivalent experience)inComputerScience, Software Engineering or Software Architecture preferred; candidates with substantial and relevant industry experience are also eligible The overall experience for the candidate to be 10-12 years Eight years ofengineering experience Experience in at least one of these AI / ML platform: Databricks, Snowflake, AWS SageMaker, Azure ML Studio, and other emerging technology is a must Bachelors degree in Computer Science, Mathematics, Statistics, Operations Research. 3 years of experience as a ML Engineer or MLOps Engineer or in a similar role. 3 years experience in Databricks. Mastery in SQL Programming Language (like when to use OUTER JOIN and when to use NOT EXISTS) Experience with Snowflakes. Proficiency in Python. Experience with any of cloud systems Azure, AWS or GCP. 3 years experience in Azure is preferred. Experience with data wrangling in Pandas or PySpark dataframe. Experience with feature engineering or building out a feature store Experience with ML model training, tuning, and registration in Databricks MLFlow and Databricks Unity Catalog Experience with DevOps MLOps process by programmatically promoting the code from DEV to QA to PROD environments Knowledge of data management fundamentals, data storage principles, ETL, Data Modeling, and Data Architecture. Excellent problem-solving skills, combined with the ability to present your findings/insights clearly and compellingly in both verbal and written form. Exhibit Entrepreneurship at every level of work.

Location: bangalore, IN

Posted Date: 6/12/2025