Top Real Estate Data Engineering Jobs in Austin, TX

The Principal Data Engineer will lead the technical strategy for data initiatives, focusing on real-time data platforms and collaboration with stakeholders to design efficient and innovative data architectures, ensuring data governance and compliance.

As a Senior Data Engineer, you will design and maintain scalable data models, build production data pipelines, and support analytics across various business functions.

In this role, you'll build and scale high-throughput data pipelines, ensure data quality, and leverage AI for improved data operations. You'll also lead initiatives in a fast-paced environment focused on real estate data engineering.

The Data Implementation Specialist manages data discovery and migration for PRISM platform projects, ensuring client satisfaction through innovative data solutions and effective communication.

The Data Engineer will build the data infrastructure, including ingestion pipelines and backend services, while ensuring data accessibility and quality for the company.

The role involves managing data infrastructure, building data pipelines, providing analytics to inform business decisions, and shaping AI workflows in the organization.

The Senior Analytics Engineer will lead data initiatives, manage analytics platform roadmaps, and create reliable data models while ensuring high-quality insights for stakeholders.

Lead Analytics Engineer responsible for end-to-end data solution design, evolving data architecture, mentoring engineers, driving data health and observability, enabling cross-functional measurement, and contributing to roadmap and decision-making.

Lead design and delivery of enterprise data centralization and automation for reporting and BI. Build and maintain ETL/SSIS pipelines, data orchestration, file delivery and quality controls, follow SDLC/agile, mentor junior engineers, and partner with business stakeholders to capture requirements and ensure timely data delivery.

Lead design and delivery of a cloud-based data platform: implement CDC/streaming ingestion, modeling, transformations, cross-region DB replication, observability, governance (PII, lineage, access), and enable downstream marts while mentoring engineers and driving IaC/automation-first practices.