Recruitment Optimization Stack

### Optimizing Recruitment Processes with Applicant Data.

Extract data from Applicant Tracking Systems using Airbyte, transform it with dbt, and analyze to optimize recruitment processes.

How to get started:

- Check out the [README](https://github.com/airbytehq/quickstarts/tree/main) and the [Contribution instructions](https://github.com/airbytehq/quickstarts/blob/main/CONTRIBUTING.md) in this repo.
- Check one of the [existing quickstarts](https://github.com/airbytehq/quickstarts#list-of-available-quickstarts) and observe their structure.
- (Optional, but highly recommended) Implement one of the quickstarts by following the instructions in their README. I recommend starting with [E-commerce analytics in BigQuery](https://github.com/airbytehq/quickstarts/tree/main/ecommerce_analytics_bigquery)

Start with the repository README and CONTRIBUTING.md, then inspect the existing quickstarts and the recommended ecommerce_analytics_bigquery quickstart. Define the new quickstart around extracting Applicant Tracking System data with Airbyte, transforming it with dbt, and analyzing recruitment processes; it is done when the quickstart follows the repository's established structure and includes usable instructions.

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