Greenhouse Source (docs)

This package models Greenhouse recruiting data from Fivetran's connector. It uses data in the format described by this ERD.

This package enriches your Fivetran data by doing the following:

• Adds descriptions to tables and columns that are synced using Fivetran
• Adds column-level testing where applicable. For example, all primary keys are tested for uniqueness and non-null values.
• Models staging tables, which will be used in our transform package

Models

This package contains staging models, designed to work simultaneously with our Greenhouse modeling package. The staging models:

• Remove any rows that are soft-deleted
• Name columns consistently across all packages:
  • Boolean fields are prefixed with is_ or has_
  • Timestamps are appended with _at
  • ID primary keys are prefixed with the name of the table. For example, a user table's ID column is renamed user_id.
  • Foreign keys include the table that they refer to. For example, an application's recruiter user ID column is renamed recruiter_user_id.

Installation Instructions

Include in your packages.yml

packages:
  - package: fivetran/greenhouse_source
    version: [">=0.4.0", "<0.5.0"]

Configuration

By default, this package looks for your Greenhouse data in the greenhouse schema of your target database. If this is not where your Greenhouse data is, add the following configuration to your dbt_project.yml file:

# dbt_project.yml

...
config-version: 2

vars:
    greenhouse_database: your_database_name
    greenhouse_schema: your_schema_name 

Passthrough Custom Columns

The Greenhouse APPLICATION, JOB, and CANDIDATE tables may have custom columns, all prefixed with custom_field_. To pass these columns along to the staging and final transformation models, add the following variables to your dbt_project.yml file:

# dbt_project.yml

...
config-version: 2

vars:
    greenhouse_application_custom_columns: ['the', 'list', 'of', 'columns'] # these columns will be in the final application_enhanced model
    greenhouse_candidate_custom_columns: ['the', 'list', 'of', 'columns'] # these columns will be in the final application_enhanced model
    greenhouse_job_custom_columns: ['the', 'list', 'of', 'columns'] # these columns will be in the final job_enhanced model

Disabling Models

Your Greenhouse connector might not sync every table that this package expects. If your syncs exclude certain tables, it is because you either don't use that functionality in Greenhouse or have actively excluded some tables from your syncs.

To disable the corresponding functionality in the package, you must add the relevant variables. By default, all variables are assumed to be true. Add variables for only the tables you would like to disable:

# dbt_project.yml

...
config-version: 2

vars:
    greenhouse_using_prospects: false # Disable if you do not use prospects and/or do not have the PROPECT_POOL and PROSPECT_STAGE tables synced
    greenhouse_using_eeoc: false # Disable if you do not have EEOC data synced and/or do not want to integrate it into the package models
    greenhouse_using_app_history: false # Disable if you do not have APPLICATION_HISTORY synced and/or do not want to run the application_history transform model
    greenhouse_using_job_office: false # Disable if you do not have JOB_OFFICE and/or OFFICE synced, or do not want to include offices in the job_enhanced transform model
    greenhouse_using_job_department: false # Disable if you do not have JOB_DEPARTMENT and/or DEPARTMENT synced, or do not want to include offices in the job_enhanced transform model

Note: This package only integrates the above variables. If you'd like to disable other models, please create an issue specifying which ones.

Changing the Build Schema

By default this package will build the Greenhouse Source staging models within a schema titled (<target_schema> + _greenhouse). If this is not where you would like your staging models to be written to, add the following configuration to your dbt_project.yml file:

# dbt_project.yml

...
models:
    greenhouse_source:
        +schema: my_new_staging_models_schema # leave blank for just the target_schema

Contributions

Don't see a model or specific metric you would have liked to be included? Notice any bugs when installing and running the package? If so, we highly encourage and welcome contributions to this package! Please create issues or open PRs against main. See the Discourse post for information on how to contribute to a package.

Database Support

This package has been tested on BigQuery, Snowflake and Redshift.

Resources:

• Provide feedback on our existing dbt packages or what you'd like to see next
• Have questions, feedback, or need help? Book a time during our office hours using Calendly or email us at [email protected]
• Find all of Fivetran's pre-built dbt packages in our dbt hub
• Learn how to orchestrate dbt transformations with Fivetran
• Learn more about Fivetran overall in our docs
• Check out Fivetran's blog
• Learn more about dbt in the dbt docs
• Check out Discourse for commonly asked questions and answers
• Join the chat on Slack for live discussions and support
• Find dbt events near you
• Check out the dbt blog for the latest news on dbt's development and best practices