Senior Data Engineer

Job Posting:

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

Ferguson is a Fortune 500 company providing best-in-class products, services, & capabilities across multiple industries including Commercial/Mechanical, Facilities Supply, Fire & Fabrication, HVAC, Industrial, Residential Trade, Residential Building & Remodel, Waterworks, & 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 Reporting & Analytics organization supports the business by developing scalable data & reporting solutions that help teams better understand performance & make informed decisions. Our teams focus on building practical, high-quality analytics tools in a collaborative environment where technical excellence, ownership, & continuous improvement are valued. At Ferguson, you will have the opportunity to build a career you are proud of at a company you can believe in.

Location:

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

Job Summary:

The Senior Data Engineer is an advanced individual contributor responsible for designing & developing complex semantic models & scalable reporting solutions. This role owns technical solution design within assigned workstreams & ensures delivered solutions meet performance, quality, & maintainability standards. This role will provide technical guidance to other developers, contribute to advanced analytics & predictive modeling initiatives, & play a key role in maintaining consistency & 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-drive querying, ensuring datasets include standardized metrics, well defined relationships & rich metadata.

Qualifications:

• Bachelor’s degree in Computer Science, Information Systems, Data Analytics, or equivalent experience.
• Advanced expertise in SQL & DAX.
• 3–6 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.
• Prove