SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Build is an AI company creating an agentic AI stack for institutional real estate, automating complex development and acquisitions workflows. The company partners with major alternative asset investors, developers, and governments to accelerate built-world projects including digital infrastructure, energy, and industrial development.
In this role, you will own Build's real estate data layer—the foundation that transforms fragmented data sources into a single, trusted picture of every site and asset. You'll work alongside geospatial specialists and domain experts to ingest, clean, link, and cross-reference property records, land data, power capacity information, planning and zoning portals, grid and utility data, transaction comparables, and geospatial layers.
Key responsibilities include:
- Building and maintaining the real estate data layer: ingesting, cleaning, linking and cross-referencing property, land, power, planning and market data sources into one unified record per site and asset
- Entity resolution and data quality: matching parcels, owners, titles and addresses across fragmented sources, and flagging conflicts and gaps before they reach decision-makers
- Developing intelligence layers on top of raw data: comps selection, valuation and NOI inputs, distress and pricing-gap signals, and risk/red-flag detection that power Build's AI workflows and expert users
- Finding, evaluating and onboarding new data sources to make Build's site validation faster and more accurate than competitors
- Ensuring speed, reliability and coverage as Build expands into new markets
You'll work in an environment that values velocity, excellence, long-term thinking, ownership, customer passion, integrity, trust, and measurable results. Build emphasizes radical autonomy, minimal bureaucracy, and meaningful equity alongside competitive compensation.
Requirements:
- Background as a data engineer or data scientist at a real estate data company with experience stitching together property records at scale, OR an engineer on research/analytics/data teams at brokerages, investors or advisory firms, OR a geospatial/ML engineer who has built valuation or site selection models on messy real-world data
- Typically a CS, data engineering or similarly technical background
- A few years of professional experience
- Genuine curiosity about how the built world gets valued and constructed
- Ability to work with intensity, move fast, and maintain high standards
