Company Overview:
Hillwood, a Perot Company, is a premier real estate investment and development company founded on a culture of integrity, respect, excellence and teamwork. The company is a full-service real estate developer, investor and advisor focused on developing opportunities for investors, partners and communities around the world. See additional details at www.hillwood.com.
Position Summary:
Hillwood IT is seeking an experienced Senior Business Intelligence Engineer (AIâNative Analytics) to join our team in Dallas, TX to play a highâvisibility role at the center of the company’s data strategy. This position is responsible for designing and delivering executiveâgrade analytics used by executive and senior leadership, translating complex real estate and financial data into clear, actionable insights that support critical decisionâmaking.
The Senior BI Engineer will blend deep business intelligence engineering expertise with strong business acumen and modern, AIâenabled analytics. Serving as a trusted partner to executive stakeholders, this role will lead discovery conversations, shape reporting requirements, and ensure every deliverable meets boardâlevel standards for accuracy, clarity, and design quality. The ideal candidate brings both technical depth and executive polish, discerning when a traditional dashboard is sufficient and when AIâpowered, conversational, or embedded analytics deliver greater value. They ask strong business questions, translate ambiguity into clarity, and care deeply about both the substance and presentation of the insights delivered.
Responsibilities:
Executive Analytics and Dashboard Delivery:
- Design and build executive-facing dashboards using Power BI, Databricks AI/BI (Lakeview), and other appropriate solutions based on audience and use case.
- Lead design reviews and approve mockups with senior stakeholders prior to build.
- Ensure visual hierarchy, data accuracy, performance, and usability across all BI outputs.
- Maintain a reusable library of certified dashboards, report components, and design standards.
- Develop BI center-of-excellence practices, including self-service standards and guardrails
- Enable conversational and AI-assisted analytics experiences (e.g., Databricks Genie Spaces, chat-to-chart, voice-to-insight).
- Build and deploy Databricks Applications (Lakehouse Apps / Mosaic AI) to embed analytics into operational workflows.
Data Modeling and Semantic Layer:
- Build and maintain Power BI semantic models aligned to certified enterprise metrics.
- Design star schemas and dimensional models serving as