HOW YOU’LL MAKE A DIFFERENCE

• Continuously deliver, enhance, andoptimizehigh-priority enterprise data assets thatpower Columbia’sglobalanalytics, reporting and visualizationcapabilities, ensuring solutions are scalable, reliable, and alignedwith modern engineering standards

• Design, build, test, andmaintainend-to-end data management solutionsacrossColumbia’sglobal data lake anddatabricksenvironment, applying strong solution design principles, reusable design patterns, and industry-standard data modeling techniques such asKimball, Inmon,and relational/OLTPapproaches

• Identifyand communicate project risks and technical impediments early, partnering withthe Manager and cross-functional team members to ensuretimelyresolution and successful delivery within definedscope, timelines, and expectations.

• Apply Agile ways of working to iteratively refine requirements, define acceptance criteria, plan development activities, and deliver high-qualityenterprisedata solutions throughcontinuouscollaboration and incremental value delivery

• Serveasatechnical representative for DataEngineering within assigned initiatives,collaboratingclosely with architecture partners to evaluate solution options, recommend design patterns, and ensure alignment with enterprise architecture principles

• Solve complex technical problems that span multiple systems or projects, driving improvements in engineering practices, data quality,performanceand maintainabilityProvide mentorship, technical guidance, and best-practice leadership to elevate engineering capability across the team.

YOU ARE

• A professional with sound judgment and decision-makingskills

• A self-starter withanappropriate senseof urgency

YOU HAVE

• Bachelor’s DegreerequiresComputer Science, Information Systems or a relatedfieldor an equivalent combination of education and experience may be considered.

• 8+ years of hands-on experienceengineering,architecting,developingandoptimizinglarge-scale data and analytics solutions, including BI, data warehousing, or enterprise data platforms

• Expert-levelproficiencyin SQLdevelopmentand query optimization for data platforms such as Azure SQL DW,Databricks, SAP BW/HANA,Oracle,orequivalent technologiesSkilledin building optimized semantic models andAnalysis ServicesPower BIsemantic models.

• Deep understanding ofdatabaseand data modelingconcepts, including normalization, indexing, physical and logical modeling,performance tuning, and large-scale relational design

• Strong knowledge of dimensional modeling and enterprisedata warehousing techniques,including Kimball, Inmon, and relatedpractices

• Hands-on experience implementing andmaintainingstar schemas, along withexpertiseinslow changing dimensions (SCDs), late arriving data, and other warehousing patterns.

• 4+years’professionalexperiencebuildingand supportingETLELT solutionsusing toolssuch as Data Factory,Databricks,Informatica, SQL Server Integration Services, Business Objects Data Services, or IBMDatastage

• 4+years’ experiencedeveloping and supporting data visualization and analytical solutions, with strongproficiencyin Microsoft Power BI, including semantic modeling and DAX.

• Familiarity with datadomains common toCommercial, and Supply Chainenvironments,or experience integratingdata sourced from SAP ERP or Microsoft Dynamicsor similar large-scale enterprise systems.

• Experienceworking with large-scale or distributed data processing technologies,optimizingdata structures, and designing scalable data pipelines (experience with Azure cloud ecosystem strongly preferred).

• Hands-onexperience with Microsoft Azuredata services, such as Azure Data Factory, data Lake,Databricks,Synapse, or other modern cloud data platforms

• Advanced DAX skills andproficiencyin 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, orMLOpspractices

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