Real Estate Data & Intelligence Engineer
About The Position
Build is hiring a Real Estate Data & Intelligence Engineer to turn fragmented real estate and infrastructure data into a trusted, unified picture of every site and asset, and to build intelligence that helps AI workflows, experts, and clients determine what the data means and what to do next. The role works alongside geospatial colleagues and domain experts to identify relevant sources, connect and cross-reference information, uncover inconsistencies and assumptions, and produce actionable answers. The position owns the real estate data layer across property, land, power, planning, and market sources; entity resolution and data quality; and intelligence such as comparable selection, valuation and NOI inputs, distress and pricing-gap signals, and risk detection. It also involves finding and onboarding new data sources and maintaining the speed, reliability, and coverage of these capabilities as Build expands into new markets. Build describes itself as an agentic AI company serving institutional real estate and the built world. Its culture emphasizes speed, intensity, excellence, ownership, teamwork, integrity, trust, and customer focus. The company offers autonomy, meaningful equity, close collaboration with experienced teammates, and the opportunity to help shape real-world development projects.
Requirements
- A technical background in computer science, data engineering, or a similar field.
- A few years of experience.
- Curiosity about how the built world is valued and built.
- Ability to take ownership of outcomes and work with high standards, speed, and intensity.
- Ability to work effectively as part of a team and with a customer-focused mindset.
Nice To Haves
- Experience as a data engineer or data scientist at a real estate data company, stitching together property records at scale.
- Experience on a research, analytics, or data team at a brokerage, investor, or advisory firm.
- Experience as a geospatial or machine-learning engineer building valuation or site-selection models using messy real-world data.
- A personal interest in the built world, including a related hobby or story.
Responsibilities
- Ingest, clean, link, and cross-reference property, land, power, planning, and market data sources into a unified record for each site and asset.
- Match parcels, owners, titles, and addresses across sources; identify and flag conflicts and data gaps before they affect decisions.
- Develop intelligence used by AI workflows and experts, including comparable selection, valuation and NOI inputs, distress and pricing-gap signals, and risk and red-flag detection.
- Find, evaluate, and onboard new data sources to improve the speed and accuracy of site validation.
- Maintain and improve the speed, reliability, and coverage of the data layer and intelligence as Build expands into new markets.
- Work with the geospatial team and domain experts to select relevant sources, connect and cross-reference data, and convert it into actionable answers.
Benefits
- Meaningful, generous equity.
- Radical autonomy and end-to-end ownership of work.
- An accelerated opportunity to learn company-building through hands-on work.
- Collaboration with experienced, high-performing teammates.
- Extraordinary shared cultural experiences.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
