Job Description

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.

Working as part of a dedicated offshore scrum team, this engineer designs, builds, and supports curated analytical datasets that enable enterprise reporting, self‑service analytics, and advanced insights. The role partners closely with domain analytics teams, Power BI modelers, and platform architects to translate business requirements into reliable, performant data products.

This position is ideal for a hands‑on data engineer who enjoys working across multiple business domains, values strong data modeling practices, and thrives in a modern cloud‑based analytics environment.

HOW YOU’LL MAKE A DIFFERENCE

Databricks & Data Engineering Delivery

• Design, build, test, and maintain data pipelines and curated datasets using Azure Databricks to support both Supply Chain and DTC analytics
• Apply strong ELT/ETL patterns, Spark-based transformations, and Delta Lake best practices to deliver scalable, reliable data assets
• Develop and maintain dimensional models and analytical tables optimized for BI and downstream consumption
• Improve data reliability, performance, and usability through thoughtful modeling, testing, and optimization

Analytics Enablement (Supply Chain & DTC)

• Deliver prioritized enterprise data assets that support global Supply Chain and DTC analytics, reporting, and self‑service use cases
• Partner with Power BI engineers by providing well‑modeled, high‑quality datasets and supporting semantic model development
• Support troubleshooting of data and model issues that impact enterprise reporting and decision‑making

Collaboration & Agile Delivery

• Collaborate closely with Supply Chain and DTC analytics teams, business analysts, and product owners to understand requirements and deliver value iteratively
• Participate fully in Agile delivery processes, including backlog refinement, estimation, sprint execution, and retrospectives
• Identify project risks, technical blockers, and data quality issues; communicate proactively and partner on solutions

Engineering Excellence & Growth

• Follow established engineering standards, patterns, and best practices while contributing to continuous improvement
• Leverage guidance from Principal Data Engineers and Engineering Managers to grow technical depth in Databricks and cloud data engineering
• Contribute to a collaborative GCC engineering culture focused on quality, learning, and delivery

YOU ARE

• A hands‑on data engineer who enjoys building cloud‑scale analytics solutions
• Comfortable working across multiple business domains (Supply Chain and DTC)
• Collaborative, curious, and motivated to continuously improve data platforms and practices
• Effective communicating with both technical peers and analytics stakeholders

YOU HAVE

• Bachelor’s degree in Computer Science, Information Systems, or a related technical field, or equivalent practical experience
• Strong proficiency in SQL and query optimization for analytical workloads
• Hands‑on experience building data pipelines and transformations using Azure Databricks (Spark / Delta Lake preferred)
• Solid foundation in data modeling and data warehousing concepts, including dimensional modeling and star schemas
• Experience designing and supporting ETL/ELT pipelines using tools such as Azure Data Factory, Databricks, or similar platforms
• Experience working with large‑scale or distributed data processing systems
• Hands‑on experience with Azure data services, such as Azure Data Lake Storage, Azure Data Factory, and Databricks
• Experience supporting analytics or BI use cases, including familiarity with Power BI datasets or semantic models
• Working knowledge of Python or another scripting language used in data engineering workflows
• Advanced DAX skills and proficiency in languages such as Python, PowerShell, R, or Java to support automation, scripting, or advanced analytics.
• Bonus: experience with AI/ML engineering, automation agents, generative AI capabilities, or MLOps practices

#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 position's scope and function in the company.