Export Columns - Jobo Enterprise

Column Mapping

Each export column has two names:

Name	Description
sourceColumn	The internal field name used in Jobo’s database
outputName	The column header that appears in your exported file

Currently these are identical (e.g., salary_min → salary_min). Custom column renaming is planned for a future release.

Select only the columns you need to reduce file size and processing time. Exports with fewer columns are faster to generate and smaller to download, especially in CSV and JSON formats.

Available Columns

Column	Type	Description
`id`	uuid	Unique job identifier
`title`	string	Job title
`company_name`	string	Company name
`company_id`	uuid	Company identifier
`description`	string (HTML)	Full job description in HTML
`listing_url`	string	Original job listing URL
`apply_url`	string	Direct application URL
`city`	string	Job city
`state`	string	Job state/region
`country`	string	Job country (ISO 3166-1 alpha-2)
`salary_min`	number	Minimum salary
`salary_max`	number	Maximum salary
`salary_currency`	string	Salary currency code (USD, EUR, GBP, etc.)
`salary_period`	string	Salary period (yearly, monthly, hourly)
`employment_type`	string	Full-time, Part-time, Contract, Internship
`workplace_type`	string	Remote, Hybrid, On-site
`experience_level`	string	Entry, Mid, Senior, Lead, Executive
`is_remote`	boolean	Whether the job is remote
`source`	string	ATS source identifier (e.g., `greenhouse`, `workday`)
`date_posted`	datetime	When the job was originally posted
`created_at`	datetime	When added to Jobo’s system
`updated_at`	datetime	Last update timestamp

Tips for Selecting Columns

Minimal export — just the essentials

Select id, title, company_name, listing_url, city, country, and date_posted for a lightweight export suitable for quick scans or feeding into a search index.

Salary analysis

Include salary_min, salary_max, salary_currency, salary_period, title, city, country, and experience_level for compensation benchmarking.

Full record for data warehouse

Select all columns for a complete snapshot. Use Parquet format for maximum compression and query performance.

Example Record

A full JSON record with all columns selected:

{
  "id": "550e8400-e29b-41d4-a716-446655440000",
  "title": "Senior Software Engineer",
  "company_name": "Acme Corp",
  "company_id": "7c9e6679-7425-40de-944b-e07fc1f90ae7",
  "description": "<p>We are looking for a Senior Software Engineer to join our team...</p>",
  "listing_url": "https://boards.greenhouse.io/acme/jobs/123",
  "apply_url": "https://boards.greenhouse.io/acme/jobs/123/apply",
  "city": "San Francisco",
  "state": "California",
  "country": "US",
  "salary_min": 150000,
  "salary_max": 200000,
  "salary_currency": "USD",
  "salary_period": "yearly",
  "employment_type": "Full-time",
  "workplace_type": "Remote",
  "experience_level": "Senior",
  "is_remote": true,
  "source": "greenhouse",
  "date_posted": "2025-02-01T00:00:00Z",
  "created_at": "2025-02-01T12:00:00Z",
  "updated_at": "2025-02-10T08:30:00Z"
}

The description field contains HTML. If you need plain text, strip tags in your processing pipeline or use a Pipeline with a Liquid template to extract text before export.

​Column Mapping

​Available Columns

​Tips for Selecting Columns

​Example Record

Column Mapping

Available Columns

Tips for Selecting Columns

Example Record