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Built is an AI-powered platform transforming real estate finance, development, and management. The company powers 86,000+ active projects valued at over $300 billion, serving 350+ lenders, 80,000+ borrowers and owners, and thousands of contractors.
You will lead Built's growing data engineering organization, guiding a high-impact team building the industry's first holistic real estate data engine. This engine powers analytics, decisioning, workflow automation, and new product capabilities across the platform. Your team owns foundational data capabilities including ingestion, modeling, governance, reliability, and self-serve analytics infrastructure.
As a hands-on player-coach leader, you will set technical direction, grow talent, and deliver durable systems at scale while partnering closely with Product, Analytics, and Engineering leadership. You'll influence how Built captures, normalizes, and activates critical real estate finance data with autonomy and executive visibility.
Key responsibilities include leading and growing the data engineering team through coaching, hiring, and culture-building; owning the data platform strategy including architecture for ingestion, transformation, orchestration, and governance; delivering high-quality, observable, secure, and scalable systems; and partnering cross-functionally with Product, Analytics, Security, and Engineering to ensure data drives customer and business outcomes. You'll stay hands-on through architecture reviews, design docs, and occasional implementation.
The role requires 5+ years of engineering management experience in fast-paced, high-growth environments, with direct experience leading data engineering or data platform teams. You need proven ability to scale teams and systems, excellent cross-functional communication, and hands-on familiarity with Snowflake, DBT, or Sigma. Experience building modern data platforms (ELT, modeling, governance, self-serve analytics) is essential. Preferred qualifications include streaming data patterns (Kafka), AWS production systems, and exposure to AI/ML workflows. Travel is approximately 5-6 times annually, including two company-wide Connect Weeks and leadership travel to Nashville or designated locations.
