Senior Analytics Engineer (Data Platform & AI Enablement)

About the role

At Delta Faucet, we are committed to transforming everyday experiences with water through innovative products and exceptional service. As a leader in the plumbing industry, we take pride in our dedication to quality, sustainability, and customer satisfaction. We believe that diverse perspectives strengthen our mission to create solutions that inspire and elevate the lives of all our customers. We welcome individuals from all backgrounds to join us on this journey toward inclusivity and excellence.

Position Summary

The Senior Analytics Engineer owns the layer between curated enterprise data and business consumption. Working primarily in Databricks, Unity Catalog, and Power BI, this role designs and maintains certified data products, semantic models, standardized metrics, and quality controls used by analysts, self-service users, dashboards, and AI agents.

This role replaces a traditional Data Engineer position. Its primary accountability is analytics readiness and trust, rather than source ingestion or ETL throughput.

Why the Role Matters

• Creates a common, governed foundation for reporting, analysis, self-service, and AI.
• Moves repeat logic out of individual reports and into reusable certified assets.
• Reduces conflicting metrics, duplicate datasets, and analyst preparation effort.
• Enables the Decision Intelligence value stream from Intake to Insight to Impact.

Core Responsibilities

• Build and maintain certified facts, conformed dimensions, curated views, and Gold-layer data products.
• Own Power BI semantic models, shared measures, hierarchies, relationships, security, and performance.
• Translate agreed business rules and KPI definitions into transparent, testable, version-controlled logic.
• Implement Unity Catalog governance, metadata, access controls, lineage, certification, and deprecation standards.
• Automate data quality, reconciliation, freshness, and anomaly monitoring for certified products.
• Publish reusable, documented assets that support self-service analytics and governed AI consumption.

Key Partnerships

• Analysts and visualization partners: provide trusted models and absorb recurring logic into governed assets.
• Business owners and data stewards: align definitions, priorities, certification evidence, and acceptable quality.
• IT and data platform teams: define curated input contracts and resolve upstream source issues.
• AI and automation engineers: provide secure, described, retrieval-ready data for agents and workflows.

Required Qualifications

• Bachelor's degree in a quantitative or technology field, or equivalent practical experience.
• 5+ years in analytics engineering, data engineering, BI engineering, or data platform roles, including experience with curated analytics layers or semantic models.
• Advanced SQL and strong dimensional modeling skills, including fact grain, conformed dimensions, and star schemas.
• Production experience with a cloud Lakehouse or warehouse; Databricks and Delta Lake strongly preferred.
• Power BI semantic modeling experience, including DAX, relationships, security, and optimization.
• Experience with data governance, metadata, lineage, quality controls, Git, code review, and deployment discipline.
• Ability to translate business questions and metric definitions into scalable data products and plain-language documentation.

Preferred Experience

• POS, omnichannel retail, consumer products, or manufacturing data.
• Dataset certification, data product management, dbt or Lakeflow/DLT, and Databricks Workflows.
• Preparing governed data for AI agents, RAG, forecasting, or advanced analytics.