Data & Analytics Architect

- Set and evolve standards for model design, naming, calculation groups, row-level security, deployment pipelines, and lifecycle management, and recommend the right consumption pattern per use case (Import, DirectQuery, Direct Lake, composite models, aggregations). - Own performance tuning across the stack—source query design, VertiPaq compression, DAX/MDX efficiency, and refresh strategy—using tools like DAX Studio, Tabular Editor, VertiPaq Analyzer, and SQL Profiler. - Set performance benchmarks, monitoring, and capacity planning for Power BI Premium, Fabric, and Azure Analysis Services, guiding partitioning, aggregation, incremental refresh, and storage mode decisions for large, high-concurrency models.

- Set performance benchmarks, monitoring, and capacity planning for Power BI Premium, Fabric, and Azure Analysis Services, guiding partitioning, aggregation, incremental refresh, and storage mode decisions for large, high-concurrency models. - Author advanced DAX/MDX, complex Power Query (M), and T-SQL, and build proof-of-concept models that prove out the architecture before handing off to development. - Review and guide semantic models and report architecture built across Insights Engineering and partner towers, and contribute to high-priority initiatives like the Power BI Center of Excellence and Lakehouse consumption strategy.

- Deep hands on expertise with Power BI semantic models, including advanced DAX, Power Query (M), and Tabular Editor. - Strong experience designing and tuning tabular models in Azure Analysis Services or SQL Server Analysis Services. - Working knowledge of multidimensional OLAP cubes and MDX, with the ability to support and modernize legacy cube workloads.

- Proven experience designing dimensional models (star schema, fact and dimension design, slowly changing dimensions, aggregations). - Strong SQL skills for data profiling, query design, and source side optimization. - Demonstrated success diagnosing and resolving complex performance issues across the BI stack.

- Experience with Microsoft Fabric, Direct Lake, OneLake, and Lakehouse based consumption architectures. - Experience integrating Power BI with Snowflake, Databricks, Azure Synapse, or Azure SQL. - Familiarity with CI/CD for analytics (Git, TMDL, deployment pipelines, Tabular Editor automation).

How you will make an impact: - Lead the design of enterprise-grade semantic and tabular models across Power BI, Microsoft Fabric, and Azure Analysis Services—prioritizing reusability, governance, and long-term maintainability. - Architect dimensional models (star/snowflake) that support both modern tabular workloads and legacy OLAP cubes still in production.

- Own performance tuning across the stack—source query design, VertiPaq compression, DAX/MDX efficiency, and refresh strategy—using tools like DAX Studio, Tabular Editor, VertiPaq Analyzer, and SQL Profiler. - Set performance benchmarks, monitoring, and capacity planning for Power BI Premium, Fabric, and Azure Analysis Services, guiding partitioning, aggregation, incremental refresh, and storage mode decisions for large, high-concurrency models. - Author advanced DAX/MDX, complex Power Query (M), and T-SQL, and build proof-of-concept models that prove out the architecture before handing off to development.

- Author advanced DAX/MDX, complex Power Query (M), and T-SQL, and build proof-of-concept models that prove out the architecture before handing off to development. - Review and guide semantic models and report architecture built across Insights Engineering and partner towers, and contribute to high-priority initiatives like the Power BI Center of Excellence and Lakehouse consumption strategy. - Serve as the technical sounding board across EDAIx—moving across projects to unblock the team, troubleshoot live issues, and pair on complex modeling problems.

- Partner with Data Engineering, Data Product, and Data Governance to shape upstream structures that simplify downstream analytics, and translate decisions into clear documentation, patterns, and reusable templates. - Define and enforce semantic layer governance (certified datasets, metric definitions, version control, release standards), champion architectural quality and accountability for what reaches production, and track the Microsoft analytics roadmap (Fabric, Direct Lake, Copilot for Power BI, semantic link) to recommend adoption. What you’ll need (Required):

- 8+ years of experience in business intelligence, analytics engineering, or data architecture, with meaningful time spent in an architect level capacity. - Deep hands on expertise with Power BI semantic models, including advanced DAX, Power Query (M), and Tabular Editor. - Strong experience designing and tuning tabular models in Azure Analysis Services or SQL Server Analysis Services.

- Familiarity with CI/CD for analytics (Git, TMDL, deployment pipelines, Tabular Editor automation). - Exposure to Power BI Embedded, Power BI REST APIs, and tenant or capacity administration. - Experience working in regulated industries such as medical devices, pharmaceuticals, or healthcare.

- Experience working in regulated industries such as medical devices, pharmaceuticals, or healthcare. - Experience contributing to or operating a Power BI Center of Excellence - Strong troubleshooting instincts and the patience to find the real root cause, not just the visible symptom.