Python Data Engineer for Automated Denue Inegi Dataset to Airtable Integration

We are seeking a skilled Python Data Engineer to develop and implement an automated solution for extracting, filtering, and delivering specific data from the denue inegi dataset into an airtable base. The primary objective is to obtain a highly curated dataset of Mexican companies based on precise criteria. Key Responsibilities: Develop Python scripts to access and process the denue inegi dataset. Implement robust filtering logic to identify companies that meet the following criteria: Located in Mexico. Have between 75 and 400 employees. Are 10 years old or older. Belong to a specified list of SCIAN codes (to be provided). Exclude companies from another specified list of SCIAN codes (to be provided). Integrate the filtered data into an existing Airtable base. The schema for the Airtable base will be provided. Set up an automated process for quarterly data refreshes. Configure an email notification system to alert us upon the successful completion of each quarterly refresh. The ideal freelancer will have strong experience in Python data engineering, data manipulation, API integration, and setting up automated workflows. Familiarity with Mexican business data sources like inegi denue is a plus.