Large-Scale Business Contact Scraping

I need an experienced data-scraping professional to pull a high volume of business contacts from three primary sources: company websites, LinkedIn, and reputable online directories. For every contact you capture, I require three data points—email address, direct phone number, and current job title—delivered in a clean, de-duplicated spreadsheet.

You are free to choose your preferred stack (Python, Scrapy, Selenium, BeautifulSoup, LinkedIn API, or equivalent) as long as it respects source-site terms and returns accurate, verifiable data. Please factor in any rate-limiting or captcha challenges up front and let me know how you plan to overcome them so the process runs smoothly at scale.

Deliverables
• CSV or XLSX file containing all scraped records, properly formatted and validated
• Brief methods summary outlining the workflow, tools, and safeguards used

Acceptance Criteria
• 100 % of rows include a working email, phone, and job title
• Less than 1 % duplication across the final dataset
• Spot checks on at least 50 random records must match live source information

If you have past examples of large contact lists you’ve built—or automated scripts that handle similar volumes—share those details in your proposal. I’m ready to move quickly once I confirm your approach fits the scope.