Sr Data Engineering Ops Engineering Ops

About The Position

Although were an apparel and footwear-focused company, technology is central to everything we do. Columbia Sportswear’s Digital Technology (CDT) group enables an IT infrastructure and applications 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 Sr. Data Operations Engineer is a member of the Data & Analytics team that is responsible for data and business intelligence design, development and testing of new capabilities/enhancements to existing solutions that meet CSCs business needs within an Agile environment. The Sr. Data Operations Engineer is responsible for investigating, documenting, and resolving production issues affecting enterprise data assets. The Sr. Data Operations Engineer will provide Tier 1 and 2 support to enterprise data assets and systems across D&A team, including critical processes and job failures. Responsibility to be on call rotation with offshore supporting during off hours. The Sr. Data Operations Engineer will work with fellow BI Engineers onsite and offshore. The Sr. Data Operations Engineer will also work closely with several enterprise support organizations and Columbia users in addition to the D&A team. Work independently and acts as a resource for co-workers with less experience.

How You’ll Make a Difference

• Provide Tier 1 and Tier 2 support to enterprise data assets and systems across the D&A team, including triage and resolution of pipeline failures, job errors, and data quality issues for solutions within the D&A environment spanning Azure, SAP BW/HANA, and BI platforms
• Investigate, document, and escalate production issues affecting enterprise data assets, building toward independent Tier 3 resolution capability over time
• Participate in Azure environment refresh and cutover activities for system integration testing and go-live events across major and minor releases
• Execute and oversee routine maintenance tasks, including backups and updates
• Implementing and managing data governance policies.
• Configuring and managing integrations with external data sources
• Lead deployments, monitor logs, and ensure timely reporting of issues
• Implement automated solutions using Python or PowerShell scripting within the Azure environment
• Collaborate with onsite and offshore team members, enterprise support organizations, and business stakeholders to resolve issues and communicate status effectively
• Contribute to operational documentation and support knowledge transfer within the team
• Act as a resource and informal mentor for less experienced team members
• Availability to participate in an on-call rotation for production support coverage
  
  

• Bachelor’s degree in computer science, Engineering, or a related field, or equivalent demonstrable experience
• 4+ years of experience in data operations, data engineering, or BI support roles, with at least 2 years in a Tier 2 production support capacity
• Hands-on experience with core Azure data services, including Azure Data Factory, Azure Data Lake Storage, and Azure Databricks
• Working knowledge of Delta Lake concepts and lakehouse architecture patterns
• Solid SQL skills including query writing, optimization, and pipeline debugging
• Experience with Python or PowerShell for scripting and automation tasks
• Familiarity with CI/CD pipelines and version control practices (Git or equivalent)
• Experience with enterprise job scheduling platforms (Tidal, Autosys, Control-M, or similar)
• Experience with Power BI or comparable BI and reporting tools
• Ability to work effectively in an Agile/scrum environment
• Good communication skills; able to collaborate with business stakeholders, support teams, and offshore counterparts
• Availability to participate in an on-call rotation for production support coverage
  
  

• Experience with SAP environments (BW, HANA, Data Services, or BOBJ)
• Exposure to Unity Catalog or enterprise data governance concepts
• Familiarity with Azure Analysis Services or comparable semantic layer tooling
• Experience working in a hybrid onshore/offshore operating model