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 ensureaccurate, scalable,high‑performanceself‑serviceanalytics.

• Lead design reviews forhigh‑impactsemantic models, influencing BI architecture decisions and ensuring alignment with enterprise data and analytics strategy.

Analytics Enablement & Collaboration

• Define andmaintainsemantic 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 onoptimalmodel consumption patterns, performance considerations, and advanced capabilities

• Champion enterprise metric consistency and help resolve cross-domain data definition misalignment

• Proactivelyidentifyand 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 tooptimizedatasets 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

• InfluenceAgile deliveryplanning,processes, including backlog refinement, estimation, sprint execution, and retrospectives

• Proactivelyidentifydata issues, technical risks, and improvement opportunities, escalating appropriately

• Astrategic, collaborative leader whoanticipatesscaling challenges and raises capability across teams

  YOU ARE

  • A recognizedexpert in BI semantic modeling and analytics data design

  • A systems thinker whooptimizesfor 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

  • Strongproficiencyin 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

  • Strongworkingknowledge and experiencewith 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

  • Experienceoperatingin a Global Capability Center (GCC) or distributed Agile team

  #LI-SA1

  #Hybrid