Principal Data Engineer at D. R. Horton in Arlington, TX

Job description

D.R. Horton, Inc., the largest homebuilder in the U.S., was founded in 1978 and is a publicly traded company on the New York Stock Exchange. It is engaged in the construction and sale of high-quality homes designed principally for the entry-level and first time move-up markets. The Company also provides mortgage financing and title services for homebuyers through its mortgage and title subsidiaries. Please visit our website at www.drhorton.com for more information. As the nation's largest homebuilder by volume, D.R. Horton is transforming how it uses data, AI, and digital solutions for the next generation of homebuilding, and we pair the reach of a national enterprise with a culture built on local ownership, practical innovation, and deep business partnerships. Our teams focus on solutions that work in the field and deliver real results, not technology for its own sake. In this role, you'll have a critical opportunity to shape modern capabilities that will influence how the company operates for years to come. D.R. Horton, Inc. is currently looking for a Principal Data Engineer . The Principal Data Engineer will serve as a senior technical leader in building the data foundation behind this evolution. This role will define modern data engineering patterns, architect reusable data products and services, guide complex engineering decisions, and help create trusted, scalable foundations for analytics and AI. The ideal candidate is a hands-on builder who thrives in an evolving environment, can move between architecture and implementation, and can translate emerging technology into durable enterprise capability. Success in this role means a trusted, reusable set of enterprise data products with defined contracts and quality, and a team that builds on shared patterns instead of one-off pipelines. Essential Duties and Responsibilities include the following. Other duties may be assigned. Define reference patterns and engineering standards for ingestion, transformation, orchestration, testing, data products, performance, and maintainability Establish software engineering practices for data including Git, CI/CD, automated testing, observability, documentation, and code quality Design and build complex enterprise pipelines and reusable data products across core business domains; ensure systems are designed for resilience, observability, security, and enterprise-grade scale by default Lead technical design reviews and resolve high-complexity data engineering, performance, reliability, and integration issues Collaborate on architecture decisions with long-term impact on cost, scalability, regulatory compliance, and data usability Evaluate and guide adoption of major technology shifts (e.g., Fabric evolution, AI/ML data integration, real-time pipelines) Mentor engineers and accelerate the transition from report-specific pipelines toward governed reusable enterprise data products Represent the function in cross-functional discovery, architecture, governance, operational-readiness, and continuous-improvement activities as appropriate Stay current on relevant data, AI, digital, software, and industry practices and apply new capabilities when they create practical business value Facilitate opportunities where data, AI, and digital capabilities can create business value, operating with an owner's mindset and a bias toward building, testing, and learning quickly Conduct all business in a professional and ethical manner Ability to travel overnight Education and/or Experience Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field, or equivalent experience 10 or more years of data engineering, software engineering, analytics engineering, or related experience with enterprise-scale data platforms Expert SQL and strong proficiency in Python or another modern programming language Deep experience with cloud data platforms, dimensional and analytical modeling, layered (medallion) architectures and semantic layers, data