We are a commercial real estate company located in Comoralo Springs looking for an experienced web scraping specialist to help with a mid-sized project. We are interested in collecting local property listing data from roughly 30 other real estate websites. This data is formatted similarly across all of these sites and should be relatively easy to scrape. We will require scrapers that run automatically and can operate with minimal long-term maintenance. Once the data is collected, some of it will likely need to be re-formatted for consistency and combined into a single spreadsheet. We would then like to have the data dumped into an Airtable database (or something similar). The specific pieces of data that we need are as follows:
- Property address (street, city, state, zip)
- Asking sale price
- Property size (square footage)
- Lot / land size (acres)
- Property type (office, retail, etc.)
- Zoning
- Broker contact info (name, phone, email)
- Company / website name
- Flyer (url or file)
- Main property photo (url or file)
When combining this data into a master list, the following items are important to us:
- We need to remove duplicate values automatically where needed. If possible, we would like to combine the data from duplicate values if, for example, empty fields exist on one record and not the other.
- We need to be able to run these scrapers on (at least) a bi-weekly basis and keep our master database up to date.
- These scrapers will need to be able to handle varied formatting, sometimes within the same site. Sometimes data is presented in non-standard units or missing entirely. Data quality is very important to us.
Thanks
About the recuiterMember since May 20, 2018 Aniket Singh
from Lombardia, Italy
Candidate shortlisted and hiredHiring open till - Aug 17, 2021
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