$ cat jobs/senior-engineering-manager-data-built-technologies-2e5ef4296e16.json
Senior Engineering Manager, Data
Built's Mission: Connect and simplify doing business in real estate. Built is the AI-powered platform transforming the way real estate is financed, developed, and managed. Purpose-built for real estate and construction, Built began by fixing construction draw management for lenders and has grown into a comprehensive operating system addressing some of the industry’s most complex challenges. Today, Built is a partner to more than 350 lenders, over 80,000 borrowers and owners, and thousands of contractors, powering 86,000 active projects valued at more than $300 billion. Learn more at getbuilt.com . __________________________ Built is looking for a Senior Engineering Manager, Data to lead our growing data organization. In this role, you will guide a high-impact group of engineers building the industry's first holistic real estate data engine that powers analytics, decisioning, workflow automation, and new product capabilities across our platform. You will lead the data engineering team responsible for building and operating foundational data capabilities across Built, including ingestion, modeling, governance, reliability, and self-serve analytics. Your team will enable product teams and business stakeholders to confidently use data to drive outcomes, while maintaining high standards for security, quality, and performance. This is a hands-on, player-coach leader who can set technical direction, grow talent, and deliver durable systems at scale, while partnering closely with Product, Analytics, and Engineering peers. This is an opportunity to lead a team building core infrastructure that shapes the company's future. You will influence how Built captures, normalizes, and activates the most critical data in our industry, with autonomy, executive visibility, and room to innovate. If you enjoy building platforms, raising engineering maturity, and scaling both teams and systems, this role sits at that intersection. Challenge Real estate finance data is complex. It is high-v
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