Columbia Sportswear
Apparel and Footwear
Sr.DataEngineer(DeliveryEngineering-DTC)
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“Sr. Data Engineer (Delivery Engineering - DTC) at Columbia Sportswear. Skills: Power BI, Data modeling, Data engineering. Design Power BI semantic models. Develop Power BI semantic models”
Industry & Context.
Troubleshooting; Root cause analysis; Performance tuning
What They're Looking For.
Must Have
Bachelor's degree in Computer Science, Information Systems, or related technical field, or equivalent practical experience, Proficiency in SQL for analytical workloads, Hands on experience building and supporting Power BI semantic models, Familiarity working with Azure data platforms, Experience integrating data from enterprise source systems
Nice to Have
PhD preferred, Specific ML framework experience, Cloud platform certs
What You'll Do.
Design Power BI semantic models
Develop Power BI semantic models
Maintain Power BI semantic models
Apply dimensional modeling principles
Optimize DAX calculations
Own semantic model troubleshooting
Tune semantic model performance
Partner with analytics stakeholders
Partner with business stakeholders
Establish best practices for model design
Follow best practices for naming standards
Follow best practices for measure governance
Follow best practices for reusability
Translate analytical requirements into Power BI models
Advise Power BI report developers
Support data quality investigations
Perform root cause analysis
Build ELT/ETL pipelines
Support ELT/ETL pipelines
Participate in design of analytical datasets
Participate in delivery of analytical datasets
Apply Databricks transformations
Apply Spark transformations
Contribute to data engineering patterns
Participate in Agile delivery
Participate in backlog refinement
Participate in estimation
Participate in sprint execution
Participate in retrospectives
Identify technical risks
Identify improvement opportunities
Escalate issues appropriately
Collaborate within engineering team
How You'll Work.
Team & Collaboration
Analytics consumers; Analytics stakeholders; Business stakeholders; Senior engineers; Architects; Global distributed engineering team; Cross-functional agile teams
Process & Methodology
Agile, Backlog refinement, Estimation, Sprint execution, Retrospectives
Full Job Description
At Columbia, we’re as passionate about the outdoors as you are. And while our gear is available worldwide, we’re proud to be based in the Pacific Northwest, where natural wonders are our playground. Every product we make and every task we undertake is inspired by the famous words of our founder Gert Boyle: “It’s perfect. Now make it better.” As pioneers of relentless improvement, we are constantly evolving. We believe the outdoors is ours to protect and strive to keep our planet healthy. We believe in empowering people to experience the outdoors to the fullest. **ABOUT THE POSITION** 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. Success in this position requires strong communication and collaboration skills, i
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