Greenhouse Job Scraper

Every open job from any Greenhouse job board, as clean JSON. Paste a boards.greenhouse.io URL or just the board token and get title, department, office, location, pay range, posted and updated dates, the full description and the apply link for every posting.

Built for recruiters sourcing from technology and growth companies, sales teams that use hiring as a buying signal, job boards that need a direct feed instead of a scrape of a scrape, and AI agents that need job data in one shape.

Why a dedicated Greenhouse scraper

Greenhouse publishes a public job-board API, so the raw data is reachable. What this actor adds is the part that takes a day to get right yourself:

• One request per board returns every job with its full description; no per-job calls, no HTML parsing of the careers page.
• EU-hosted boards (boards.eu.greenhouse.io) are detected and read from the EU API automatically.
• Departments and offices are flattened into department, team, location and locations so you can filter without walking nested arrays.
• Pay ranges are read from Greenhouse's pay-transparency fields when a company fills them in, and parsed from the description text when it does not.
• Only-new mode, filters that run before billing, and a fail-soft run that finishes even when one board has been renamed or closed.

Finding a Greenhouse board

Open the company's careers page and click any job. If the address bar shows greenhouse.io, the first path segment is the board token. Any of these work as a source:

Shape	Example
Board URL	https://boards.greenhouse.io/stripe
New-style board URL	https://job-boards.greenhouse.io/cloudflare
A job page	https://boards.greenhouse.io/figma/jobs/5123456
EU board	https://boards.eu.greenhouse.io/company
Just the token	stripe

Companies that embed Greenhouse on their own domain still have a board token; it is in the embed script (for=token) or in the apply URL.

Input

{
  "sources": ["stripe", "https://boards.greenhouse.io/cloudflare"],
  "keywords": ["account executive", "sales"],
  "locations": ["New York", "Remote"],
  "postedWithinDays": 7,
  "onlyNew": true
}

Field	Type	Default	What it does
preset	string	custom	Employer list: custom (default), sample. custom runs the sites you list and falls back to the sample boards when the list is empty
sources	string[]	[]	Greenhouse board URLs or board tokens
keywords	string[]	[]	Keep jobs whose title contains any of these (case-insensitive)
excludeKeywords	string[]	[]	Drop jobs whose title contains any of these
locations	string[]	[]	Keep jobs whose location or office text contains any of these
departments	string[]	[]	Keep jobs whose department or team contains any of these
remoteOnly	boolean	false	Keep only jobs whose location or office says remote
postedWithinDays	integer	0	Keep only jobs first published or updated in the last N days; 0 disables
includeDescriptionHtml	boolean	false	Add the original HTML description next to the plain text
onlyNew	boolean	false	Output only jobs not seen on a previous run of this board
seenStoreName	string	greenhouse-job-scraper-seen	Key-value store that remembers seen job IDs; use one name per monitor
maxJobsPerSource	integer	0	Stop after N jobs per board; 0 means the whole board
maxConcurrency	integer	5	Boards pulled in parallel

Descriptions come with the list call, so there is no "fetch details" switch; every record has descriptionText.

Output

One record per job.

{
  "vendor": "greenhouse",
  "source": "https://boards.greenhouse.io/stripe",
  "company": "Stripe",
  "jobId": "6123456",
  "title": "Account Executive, Enterprise",
  "department": "Sales",
  "team": null,
  "location": "New York, NY",
  "locations": ["New York, NY", "NYC"],
  "remote": null,
  "employmentType": "Full-time",
  "postedAt": "2026-10-28T14:02:11.000Z",
  "updatedAt": "2026-11-03T09:15:40.000Z",
  "url": "https://boards.greenhouse.io/stripe/jobs/6123456",
  "descriptionText": "Who we are...",
  "salaryMin": 150000,
  "salaryMax": 210000,
  "salaryCurrency": "USD",
  "salaryPeriod": "year",
  "salaryText": "The annual US base salary range for this role is $150,000 - $210,000.",
  "extra": { "internalJobId": 4567890, "metadata": [] },
  "scrapedAt": "2026-11-05T01:47:38.912Z"
}

Field	Meaning
company	Company name as Greenhouse reports it
jobId	Greenhouse job ID (the number in the job URL). Stable; use it as the key. extra.internalJobId is the requisition-level ID
department, team	First and second department Greenhouse lists for the job
location, locations	Greenhouse's location name first, then every office name
remote	true when the location or an office says remote; null otherwise (Greenhouse has no remote flag)
postedAt, updatedAt	first_published and updated_at from Greenhouse, ISO 8601
employmentType	From the job's metadata when the company uses an employment-type field
salaryMin, salaryMax, salaryCurrency, salaryPeriod, salaryText	From pay-range fields or the description when published; otherwise null
extra.metadata	Every custom metadata field the company attaches to the job, untouched

A RUN_SUMMARY record in the default key-value store reports boards processed, jobs fetched, filtered, de-duplicated, skipped as already seen, and any board failures with the error text.

Pricing

Pay per event. You are charged per job record written to the dataset, plus a small actor-start event. Filtered-out jobs and already-seen jobs in only-new mode are not charged. One request per board and no proxies, so platform usage is a fraction of a cent per run.

Monitoring new postings

1. Set onlyNew to true and give seenStoreName a name for this monitor.
2. Add your filters.
3. Schedule the actor (daily, or hourly for boards you care about).
4. Connect the dataset to Google Sheets, Slack, Make, Zapier or a webhook from the Integrations tab.

The first run outputs everything on the boards and remembers it. Each later run outputs only what is new.

Limits and notes

• Public job-board API only. No login, no proxies, no candidate or private data.
• Boards that are closed, renamed or set to private return an error for that board only; the run continues.
• Greenhouse does not expose a remote flag; remote is inferred from location and office names.
• This actor reads Greenhouse boards only. For Workday, Lever, Ashby or SmartRecruiters, or for a mixed list where you do not know the ATS, use the FinData Career Site Job Scraper.

Related FinData job scrapers

Same engine, same output fields, so records from any of them can be combined.

• Workday Job Scraper
• Lever Job Scraper
• Ashby Job Scraper
• Career Site Job Scraper (any company, ATS auto-detected)
• Workday, Greenhouse, Lever, Ashby, SmartRecruiters Job Scraper (all five in one actor)

For AI agents

Every field is optional: an empty input {} runs the sample boards and returns jobs, so a first call never fails. Pick "preset": "sample" to say so explicitly. Minimal call: { "sources": ["stripe"] }. Add "keywords" and "locations" arrays to narrow. Every record has the same fields and includes the description; jobId is the stable key.

Using it from code

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('findata/greenhouse-job-scraper').call({
    sources: ['stripe', 'cloudflare'],
    keywords: ['engineer'],
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();

Works the same through the Apify API, MCP server and the Python client.