I need a senior-level specialist to harvest product data from several e-commerce sites and deliver it in a single, well-structured CSV file. The task demands production-ready techniques—think Scrapy spiders hardened with rotating proxies, Selenium or Playwright for dynamic content, and solid anti-bot countermeasures. The information I’m after is very specific: product names, prices, pictures, and SKU. Nothing less, nothing more. Your solution must run reliably at scale, cope with frequent layout changes, and leave no trace that could trigger blocks. Python is the preferred stack, but if you have a proven alternative that meets the same bar, I’m open to hearing it. To be considered, include in your proposal: • At least one example of a comparable e-commerce scraping project you’ve completed • A concise outline of the tools, libraries, and proxy strategy you plan to use • Your estimated delivery timeline, broken into milestones if helpful Deliverables will be accepted when: - The full CSV containing every requested field is validated against spot-checked product pages. - Your codebase, with README, runs successfully in a fresh environment. Generic or junior-level pitches will be ignored; I’m looking for expertise built on a minimum of three years’ real-world scraping experience.