Sr. Data Engineer (Delivery Engineering DTC)

ABOUT THE POSITION

Although were an apparel and footwear-focused company technology is central to everything we do. Columbia Sportswears 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 Sportswears 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 roles 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 YOULL 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
• Own semantic model troubleshooting performance tuning and enhancement requests in partnership with analytics and business stakeholders
• Establish and follow best practices for model design naming standards measure governance and reusability

Analytics Enablement & Collaboration

• Partner closely with analysts and product teams to translate analytical requirements into well-structured Power BI models
• Advise Power BI report developers on model usage performance considerations and platform capabilities (without building reports)
• Support data quality investigations and root cause analysis across semantic warehouse and source data layers

Data Engineering (Growth Path)

• Build and support ELT/ETL pipelines that feed Power BI semantic models using Azure Databricks Azure Data Factory and the Enterprise Data Lake
• Participate in the design and delivery of curated analytical datasets and star schemas optimized for BI workloads
• Learn and apply Databricks and Spark-based data transformations expanding capability as a full stack data engineer
• Contribute to scalable data engineering patterns while guided by senior engineers and architectural standards

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
• Collaborate effectively within a global distributed engineering team

YOU ARE

• Passionate about Power BI data modeling and analytical usability
• Comfortable working close to the business while maintaining engineering rigor
• Curious and motivated to grow beyond BI into modern data engineering
• A collaborative team member who values quality clarity and continuous improvement

YOU HAVE

• Bachelors degree in Computer Science Information Systems or a related technical field or equivalent practical experience
• Strong proficiency in SQL for analytical workloads including query optimization and data validation
• Hands on experience building and supporting Power BI semantic models including:
• Star schemas and dimensional models
• Measures calculated columns and KPIs
• Basic to intermediate DAX
• Solid understanding of data warehousing and dimensional modeling concepts including SCDs and common BI patterns
• Experience supporting self-service analytics and resolving semantic or data model related issues
• 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

• Advanced DAX optimization and performance tuning
• Exposure to data ingestion frameworks orchestration or cloud scale ELT patterns
• Experience operating in a Global Capability Center (GCC) or distributed Agile team

#LI-SA1

#Hybrid

This job description is not meant to be an all-inclusive list of duties and responsibilities but constitutes a general definition of the positions scope and function in the company.