Data​/Web Developer; On Site – Boca Raton, FL

We’re looking for a well‑rounded Data & Web Developer to join our small data team in Boca Raton, FL. The role blends three things: tracking down and scraping data that isn’t handed to you in clean form, cleaning and normalizing it into something reliable, and building the web apps, tools, and Power BI dashboards that put it in front of the people who need it.

We’re not looking for a deep specialist or a senior architect — we want a capable, versatile developer who’s comfortable owning a problem from the raw, messy source all the way through to a working tool or dashboard.

As a commercial real estate owner/operator, much of our most valuable work involves spatial and points‑of‑interest (POI) data, parcel and property records, and public‑record research. You’ll own problems end to end: finding and scraping the data, cleaning and normalizing it into dependable datasets, and then building the web interfaces and Power BI reports that let our leasing, acquisitions, and asset‑management teams actually use it.

Solid, practical engineering is the foundation — across data, the web front‑end, and reporting. What makes the role interesting is the range: some weeks you’re scraping a stubborn county portal and normalizing what comes back, others you’re shipping a dashboard or a small internal web app.

• Independently scope ambiguous business questions and determine what data could answer them — then locate, acquire, and evaluate that data, including obscure or unconventional public sources that aren’t packaged as ready‑to‑use datasets.
• Source data from public records, government and GIS portals, county property‑appraiser and parcel data, POI and spatial sources, web‑scraped material, APIs, and aerial or street‑view imagery — constructing proxy signals when a direct measurement doesn’t exist.
• Scrutinize unfamiliar data before trusting it. Test its coverage, freshness, and gaps, confirm it against other sources, and be honest about how far it can be trusted.

• Build and maintain the data pipelines that turn messy, inconsistent source data into clean, reliable, repeatable datasets — handling ingestion, parsing, deduplication, and transformation.
• Normalize and reconcile data across sources — standardizing formats, matching and de‑duplicating records, and keeping things consistent as new data comes in. Set up storage and retrieval that stays manageable as volume grows.
• Build custom, fit‑for‑purpose tools for novel problems — scrapers, parsers, matchers, and pipelines — starting with a simple working version, then hardening what proves useful into something dependable and maintainable.

• Build internal web apps and tools that let non‑technical teams search, filter, and explore the data — designing simple, usable interfaces, not just the plumbing behind them.
• Develop and maintain both the front‑end and the back‑end of these tools, wiring them up to the data, APIs, and pipelines behind them.
• Build lightweight APIs and integrations that connect our data to the tools, dashboards, and services that consume it.

• Use LLMs as practical tools where they save time — prompting, structured outputs, and simple retrieval/RAG workflows that help with parsing, extraction, and other real data tasks.
• Where it’s useful, lean on vision or multimodal models to pull information out of imagery, site plans, and scanned documents.

• Build and maintain Power BI dashboards and reports that turn the data you’ve assembled into something leasing, acquisitions, and asset management can act on day to day.
• Dig into the data you assemble to answer the underlying business question — surfacing the patterns, outliers, and signal that matter to leasing, acquisitions, or asset management.
• Verify that a solution actually answers the question before anyone relies on it — checking outputs against ground truth and catching the quiet failures, not just the obvious ones.
• Translate technical results into something the business can use, and collaborate with colleagues across the company to…