Principal Data Engineer (Delivery Engineering - DTC)
Job Description
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 Principal Data Engineer – BI is a senior technical leader within Columbia Sportswear’s Global Capability Center (GCC) and Data & Analytics organization. This role is accountable for the architecture, governance, and long-term evolution of enterprise Power BI semantic models that power trusted analytics across Commercial, Supply Chain, and enterprise business domains.
The Principal Data Engineer – BI operates at an enterprise scale—defining modeling standards, performance patterns, and best practices that are adopted across teams. This role serves as the technical authority for BI semantic modeling, ensuring that Power BI models are scalable, performant, intuitive, and aligned with upstream data engineering and downstream analytics needs.
HOW YOU’LL MAKE A DIFFERENCE
Power BI Semantic Modeling (Primary Focus)
Own the enterprise strategy and technical vision for BI semantic models, supporting Commercial, Supply Chain, and corporate analytics use cases.
Design and govern shared, reusable, and conformed semantic model layers that enable consistent analytics across domains and business functions.
Establish and enforce enterprise semantic modeling standards, encompassing dimensional modeling, DAX measures and calculation patterns, performance tuning and troubleshooting, and consistent design, naming, documentation, and reusability practices to ensure accurate, scalable, high‑performance self‑service analytics.
Lead design reviews for high‑impact semantic models, influencing BI architecture decisions and ensuring alignment with enterprise data and analytics strategy.
Analytics Enablement & Collaboration
Define and maintain semantic model governance frameworks, including naming standards, metric ownership, certification, and lifecycle management
Partner with Analytics Engineering and BI teams to ensure models are usable, discoverable, and trusted by analysts and business users
Guide Power BI report developers on optimal model consumption patterns, performance considerations, and advanced capabilities
Champion enterprise metric consistency and help resolve cross-domain data definition misalignment
Proactively identify and mitigate systemic data quality or modeling risks across semantic, warehouse, and lake layers
Data Engineering & Platform Leadership
Provide technical leadership across the end-to-end analytics data stack, from ingestion through curated datasets and semantic models
Partner with Data Architects to ensure Power BI models align with Azure Databricks, Delta Lake, and enterprise Data Lake design patterns
Influence ELT/ETL architecture decisions to optimize datasets for BI performance and usability
Lead the design of curated analytical datasets and star schemas that serve multiple downstream use cases
Evaluate new Power BI and Azure analytics capabilities and drive their responsible adoption
Technical Leadership & Ways of Working
Act as a technical mentor and coach to Senior and Mid-level Data Engineers, raising the overall bar for BI engineering
Lead by influence rather than authority, driving alignment across distributed teams
Contribute to Agile planning at a program or portfolio level, shaping technical roadmaps and sequencing
Establish patterns that reduce long-term maintenance cost and improve platform scalability
Represent BI engineering in cross-functional forums and architectural discussions
Delivery & Ways of Working
Influence Agile delivery planning, processes, including backlog refinement, estimation, sprint execution, and retrospectives
Proactively identify data issues, technical risks, and improvement opportunities, escalating appropriately
A strategic, collaborative leader who anticipates scaling challenges and raises capability across teams
YOU ARE
A recognized expert in BI semantic modeling and analytics data design
A systems thinker who optimizes for enterprise scale, consistency, and longevity
Comfortable making high-impact technical decisions amid ambiguity
A technical leader who amplifies the effectiveness of others
YOU HAVE
Required Qualifications
Bachelor’s 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:
Expert-level experience designing enterprise-scale Power BI semantic models (Star schemas and dimensional models)
Deep mastery of:
Dimensional modeling and star schemas
Complex DAX patterns and performance optimization
Strong working knowledge and experience 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 position's scope and function in the company.