Analytics Data Engineer - Finance Decision Support

Since 1953, Ferguson has been a source of quality supplies for a wide range of industries. Together, we build better infrastructure, better homes, and better businesses. We exist to make our customers’ complex projects simple, successful, and sustainable by proactively solving problems, adapting to change, and continuously improving how we serve our customers, communities, and each other.

Ferguson is a Fortune 500 company providing best-in-class products, services, and capabilities across multiple industries including Commercial/Mechanical, Facilities Supply, Fire & Fabrication, HVAC, Industrial, Residential Trade, Residential Building & Remodel, Waterworks, and Residential Digital Commerce. With approximately 36,000 associates across 1,700 locations, Ferguson is a community of people working toward a shared purpose of building something meaningful.

Within Ferguson, the Finance Reporting & Analytics organization supports the business by developing scalable data and reporting solutions that help teams better understand performance and make informed decisions. Our teams focus on building practical, high-quality analytics tools in a collaborative environment where technical excellence, ownership, and continuous improvement are valued.

This role is open to remote work across the United States or in Newport News, VA, according to company policy.

About the role

The Analytics Data Engineer - Finance Decision Support is an advanced individual contributor responsible for designing and developing complex semantic models and scalable reporting solutions. This role owns technical solution design within assigned workstreams and ensures delivered solutions meet performance, quality, and maintainability standards. This role will provide technical guidance to other developers, contribute to advanced analytics and predictive modeling initiatives, and play a key role in maintaining consistency and best practices across the reporting platform.

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-driven querying, ensuring datasets include standardized metrics, well-defined relationships, and rich metadata.

Qualifications

• Bachelor’s degree in Computer Science, Information Systems, Data Analytics, or equivalent experience.
• Advanced expertise in SQL and 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 and statistical modeling.
• Proven ability to design performant and scalable datasets.
• Experience tuning DAX, model relationships, and refresh performance.
• Strong ownership mindset for solution quality and stability.
• Design semantic models optimized for AI-driven querying, ensuring datasets include standardized metrics, well-defined relationships, and rich metadata.

Benefits

At Ferguson, we care for each other. We value our well-being just as much as our hard work. We are committed to a holistic approach towards benefits plans and programs that support the mental, physical, and financial well-being of our associates. Our competitive offering includes:

• Health, dental, and vision insurance
• Paid time off
• Life insurance
• 401(k) with a company match
• Mental health coverage
• Gender-affirming and family-building benefits
• Paid parental leave
• Associate discounts
• Community involvement opportunities

Pay

Actual pay rate may vary depending upon location. The estimated pay range for this position is $6,000.30 - $9,716.30 monthly for salaried roles. This role is bonus or incentive plan eligible. Ferguson complies with all wage regulations. The starting wage may be higher in certain locations based on local or state wage requirements.