AI-Savvy Data Engineer Needed to Run Data Imports + Scraper Package

If this task can be completed, along with payment I will provide a very positive review along with potential future works with much higher budgets. I am looking for long-term clientship. We need an AI-savvy Database/Data Engineer to help configure and run a prepared data import package that will serve as the first phase of a larger database buildout. This is not a from-scratch project — we already have schema files, source registries, table inventories, import/backfill manifests, source-to-table mappings, scraper-readiness notes, starter modules, SQL files, and handoff documentation. The job is to apply the database setup, validate the structure, connect the prepared mappings, and begin populating the database using the initial prepared import/scraper package. This first package is only the starting point. The database will continue being built up and populated over time using additional files, public APIs, downloadable datasets, and scrapeable public sources. Speed matters, so we are specifically looking for someone who can use AI tools, AI-assisted coding, and prompt engineering to move quickly — using tools like ChatGPT, Claude, Cursor, GitHub Copilot, or similar to review files, understand the package, generate/debug scripts, improve SQL, validate mappings, and accelerate implementation. The work should still be carefully checked and reliable, but we do not want a slow fully-manual workflow. This phase is raw data infrastructure only: preserve raw payloads, source rows, lineage, logs, timestamps, and deduplication fields — no signals, rankings, recommendations, forecasts, AI labels, or derived analytics yet. Please review the file attached and provide me an estimate of how much time you think it would take to set it up, connect the prepared data sources, and start importing the ticker/source data into the database. All further details will be provided in direct messages.