Build a Scalable Homeowner & Property Data Scraper

Description: I’m looking for an experienced data scraping / web automation developer to build a scalable system for collecting homeowner and residential property data from lawful public-record sources and/or licensed data sources. The scraper should be able to collect and organize fields such as: Property address Owner name Owner mailing address ZIP code / city / state Parcel/APN Single-family / property type Estimated or assessed property value Square footage Bedrooms / bathrooms when available Year built Lot size Last sale date and sale price Owner-occupied vs. absentee owner when determinable Other useful publicly available property information The system should support filtering/exporting data by ZIP code, county, city, and state. What I need Scraper capable of processing large datasets Clean CSV/database output Duplicate removal and data normalization Ability to run new ZIP codes/areas without rebuilding the scraper Error handling and automatic retries Documentation explaining how to operate it Source code provided at completion Preferably Python-based Experience with proxies, rate limiting, and large-scale scraping is a plus For any phone/email enrichment, it should use a lawful licensed provider or API rather than circumventing access controls or scraping private information.