Although we're an apparel and footwear-focused company, technology is central to everything we do . Columbia Sportswear’s Digital Technology (CDT) group enables an IT infrastructure across four global brands, a global supply chain, and 500+ geographically dispersed stores . These teams support in-store, mobile, and data platforms to enhance customer interface and service in an ever-evolving industry.
The Senior Data Engineer – Power BI is a key contributor within Columbia Sportswear’s Global Capability Center (GCC) and Data & Analytics team. This role is primarily focused on designing, building, and supporting Power BI semantic models that enable trusted, high-performance analytics across Commercial , Supply Chain and enterprise business domains.
While the role’s core responsibility is Power BI data modeling, the position is intentionally designed to grow into a full stack Data Engineer. Over time, this engineer will deepen hands-on experience across Azure Databricks, data ingestion pipelines, and the enterprise Data Lake, partnering closely with senior engineers and architects to deliver end-to-end data solutions.
This role is ideal for an engineer who enjoys working closely with analytics consumers, cares deeply about data model quality and usability, and wants to expand into modern cloud data engineering.
HOW YOU’LL MAKE A DIFFERENCE
Power BI Semantic Modeling (Primary Focus)
Design, develop, and maintain Power BI semantic models that support Commercial , Supply Chain and enterprise analytics use cases
Apply strong dimensional modeling principles (facts, dimensions, conformed dimensions) to enable intuitive, high performing ‑ self-service ‑ analytics
Develop and optimize DAX measures, calculations, and model logic to ensure accuracy, scalability, and performance
Establish and follow best practices for model design, naming standards, measure governance, and reusability
Analytics Enablement & Collaboration
Data Engineering (Growth Path)
Delivery & Ways of Working
Participate fully in Agile delivery processes, including backlog refinement, estimation, sprint execution, and retrospectives
Proactively identify data issues, technical risks, and improvement opportunities, escalating appropriately
Bachelor’s degree in Computer Science , Information Systems, or a related technical field, or equivalent practical experience
Familiarity working with Azure data platforms, such as Azure Data Lake, Azure Databricks, Azure Data Factory, or similar tools
Experience integrating data from enterprise source systems (e.g., DTC, Supply Chain, ERP, SAP, or similar domains)
Nice to Have / Growth Areas
Deeper experience with Databricks, Spark, or Delta Lake
This job description is not meant to be an all-inclusive list of duties and responsibilities, but constitutes a general definition of the position's scope and function in the company.
