> Markdown version of [/jobs/ext/4013979-principal-data-engineer](https://www.wearedevelopers.com/jobs/ext/4013979-principal-data-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Principal Data Engineer - **Company:** D. R. Horton - **Location:** United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Data Analysis, Automation of Tests, Microsoft Azure, Software Quality, Information Systems, Continuous Integration, Information Engineering, Data Integration, Extract Transform Load (ETL), Github, Python (Programming Language), Performance Tuning, Cloud Services, Software Engineering, SQL Databases, Data Streaming, Unstructured Data, Snowflake, Git, Data Layers, Build Management, Information Technology, Apache Kafka, Data Management, Programming Languages - **Published:** October 29, 2026 - **Apply:** https://drhorton.taleo.net/careersection/2/jobdetail.ftl?job=2605591 ## About the Role * 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 contracts, orchestration, CI/CD, testing, performance tuning, and data quality * Demonstrated technical leadership through architecture, standards, mentoring, and delivery of complex production systems * Demonstrated ability to work independently, take ownership, communicate clearly, and deliver results in an evolving environment * Ability to build trusted relationships across the organization, balancing enterprise standards with business needs and operating realities, * Experience with Snowflake, dbt, Fivetran or comparable ELT tools, Airflow/Dagster or comparable orchestration, Kafka/CDC and streaming, Azure, GitHub, APIs, Iceberg and open table formats, unstructured data pipelines for AI, AI-assisted development, or comparable technologies * Experience in homebuilding, real estate, construction, mortgage, title, land development, sales, purchasing, finance, customer care, or another distributed operating business is a plus * Experience working in a large enterprise with complex enterprise environments is preferred * Experience founding, incubating, or building new products, capabilities, or businesses from the ground up is a plus. ## Description * 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