Python Data Scraping Web+PDF from Public Filings

Scraping public US investment fund tax supplements and webpages. These are oftentimes PDFs or basic HTML tables. Looking for an engineer that can provide: normalized extracted data and a runnable Python file or Jupyter notebook that generates it from a list of fund issuers. Accuracy is crucial and pure LLM solutions are too inaccurate. Expertise in extracting tabular data accurately, web scraping, Python, and working asynchronously are all required. Nice to have but not required: - Data engineering experience with ability to manage and create scalable process helping us make timely updates to fund tax information for our customers - Experience with EDGAR filings - US personal tax and investment industry domain knowledge