Senior Data Engineer

Location: Bengaluru

Company Overview:
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 Enterprise, 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.

LEVEL 2 – Senior (Senior Data Engineer)

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 work streams & ensures delivered solutions meet performance, quality, & maintainability standards. Senior Engineers 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.

Essential Duties & Responsibilities:

Skills &

Qualifications:

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.
Bachelor's degree in Computer Science, Information Systems, Data Analytics, or equivalent experience.
Advanced expertise in SQL & DAX, Power BI
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 Direct Query).
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.