Project Overview: We are looking for an experienced Python developer with strong skills in automation and data extraction to build a secure, scalable application capable of scraping publicly available LinkedIn profile data using only profile URLs as input. The tool must handle large-scale scraping (up to 500,000 profiles in 24 hours) while operating safely within platform and network constraints. Key Responsibilities:---- Design and develop a LinkedIn public data scraper that accepts LinkedIn profile URLs as input. Implement distributed scraping architecture with proxy rotation, rate limiting, and user-agent spoofing to prevent detection. Integrate request queuing and parallel processing for scalable performance. Ensure that only publicly accessible information is scraped (no login or private data). Create data export functionality (CSV/JSON/API). Optimize for speed and safety while maintaining data accuracy and stability. Requirements: Strong experience in Python, Selenium, and asynchronous scraping frameworks (e.g., Playwright, Asyncio, or Scrapy). Experience with IP rotation and proxy management solutions. Proven track record building high-volume scraping or data automation systems. Knowledge of browser automation and human-behavior simulation. Secure data handling and compliance awareness regarding scraping ethics and platform policies. Ability to design for cloud deployment or distributed running environments (e.g., AWS, DigitalOcean, or VPS clusters).