Analytics Data Engineer - Finance Decision Support

Ferguson is a Fortune 500 company providing best-in-class products and services across multiple industries. The Analytics Data Engineer - Finance Decision Support is responsible for designing and developing complex semantic models and scalable reporting solutions, ensuring they meet performance, quality, and maintainability standards.

Responsibilities:

• Design and develop complex Power BI semantic models and scalable reporting solutions leveraging curated Databricks Lakehouse layers (Silver/Gold) and enterprise data sources
• Write advanced SQL (including Databricks SQL) and DAX to implement complex business logic, standardized calculations, and reusable metrics
• Architect and maintain shared semantic models and datasets that enable consistent, scalable, and reusable analytics across reporting solutions
• Apply advanced modeling techniques including calculation groups and complex dimensional structures aligned to Lakehouse-based data design
• Diagnose and resolve performance issues across Databricks and Power BI, including query optimization, model efficiency, refresh performance, and data volume management
• Collaborate with data engineering teams to define and consume curated Gold-layer datasets, ensuring alignment with reporting and analytics requirements
• Refactor existing reports and datasets to transition from isolated imports to governed semantic models built on Databricks-backed data products
• Implement and enforce dataset governance practices including certification, documentation, lineage awareness, and metric standardization
• Develop and validate data quality checks across Silver and Gold layers, identifying and addressing upstream data issues
• Design and implement automated analytical workflows integrating Power BI, Python, Databricks, and the Power Platform
• Build forecasting, trend analysis, and statistical models supporting advanced and predictive analytics use cases
• Perform code reviews and provide technical guidance to Associate developers, ensuring adherence to modeling, DAX, and reporting standards
• Design semantic models optimized for AI-drive querying, ensuring datasets include standardized metrics, well defined relationships & rich metadata

Requirements:

• Bachelor's degree in Computer Science, Information Systems, Data Analytics, or equivalent experience
• Advanced expertise in SQL & DAX
• 2-4 years of Power BI development experience
• Experience working with modern data platforms such as Databricks and querying data using Databricks SQL
• Understanding of Lakehouse architecture concepts, including Bronze, Silver, and Gold data layers
• Experience integrating Databricks data with Power BI semantic models (Import and DirectQuery)
• Familiarity with distributed data processing concepts and performance considerations for large-scale datasets
• Experience using Python or R for predictive analytics & statistical modeling
• Proven ability to design performant & scalable datasets
• Experience tuning DAX, model relationships, & refresh performance
• Strong ownership mindset for solution quality & stability
• Design semantic models optimized for AI-drive querying, ensuring datasets include standardized metrics, well defined relationships & rich metadata