Greenhouse Jobs Scraper

Greenhouse Jobs Scraper collects every open job from any company that hires through Greenhouse. Give it a list of companies (the board name from their careers URL, such as airbnb in job-boards.greenhouse.io/airbnb, or the full URL) and get each job's title, company, locations, departments, offices, posting and update dates, published salary range, full description (text and HTML) and apply link.

People also look for this as a Greenhouse API, a Greenhouse job board scraper, a Greenhouse careers page scraper, an ATS jobs API or a company job feed. It reads Greenhouse's public job board data directly, with no browser, so a 200-job company finishes in under 10 seconds. Filters for title, location, department and posting date keep only the jobs you care about, and an only-new mode turns it into a daily job feed.

This is an independent tool. It is not affiliated with, endorsed by or sponsored by Greenhouse. It reads the public job boards that companies publish for applicants.

What data you get

Every job is one row in the dataset. The fields below come from real test runs of the current build (23 test runs, 1,700+ jobs from 16 companies including Airbnb, Anthropic, Stripe, Discord, Coinbase, Reddit, Datadog and Cloudflare).

Field	Type	What it holds	Example
id	string	Greenhouse job ID, stable across runs	8917177002
title	string	Job title	Associate Commercial Counsel
organization	string	Company name	Discord
board	string	Greenhouse board name the job came from	discord
url	string	Public job page (the company's own careers page when it has one)	https://job-boards.greenhouse.io/discord/jobs/8917177002
apply_url	string	Link straight to the application form	https://job-boards.greenhouse.io/discord/jobs/8917177002#app
date_posted	string	When the job was first published (ISO)	2026-11-03T16:27:16.000Z
date_updated	string	When the job was last updated (ISO)	2026-11-03T16:31:51.000Z
locations	array	Every location given: the job's location and its offices' full addresses	["San Francisco Bay Area or Remote (U.S.)", "San Francisco, California, United States"]
location	string	The location line shown on the job	San Francisco Bay Area or Remote (U.S.)
departments	array	Departments the job belongs to	["Legal"]
offices	array	Office names	["San Francisco, CA"]
salary_min	number or null	Lowest pay in the published range	200000
salary_max	number or null	Highest pay in the published range	225000
salary_currency	string or null	Currency of the range	USD
salary_title	string or null	Label the company gives the range	Base Salary
requisition_id	string or null	The company's internal requisition number	R-107469
internal_job_id	string	Greenhouse's internal job ID (shared by reposts of the same job)	6572884002
language	string	Language of the posting	en
metadata	object	Custom fields the company publishes (e.g. team, workplace type)	{"Team": "People Success"}
description_text	string	Full job description as plain text, with line breaks and bullets	Discord has a highly engaged community…
description_html	string	Full job description as HTML	<div class="content-intro"><p>…
source	string	Always greenhouse	greenhouse
scrapedAt	string	ISO timestamp of the scrape	2026-11-08T23:03:33.251Z

Fill rates in testing: id, title, organization, url, apply_url, date_posted, date_updated, locations, location, departments, offices, internal_job_id, language, description_text and description_html were filled for 100% of jobs. requisition_id was filled for about 95%. The salary fields are filled when the company publishes a pay range on Greenhouse: 100% for Coinbase and Robinhood, 83% for Airbnb and Reddit, 0% for companies that don't publish pay. The actor never guesses a salary.

Field names follow the snake_case style of the most-used Greenhouse job APIs in the Apify Store (title, organization, url, date_posted, locations, description_text, description_html), so you can switch without rewriting your pipeline.

How to use it

1. Find the company's Greenhouse board. Open its careers page: if job links go to job-boards.greenhouse.io/<name> or boards.greenhouse.io/<name>, the <name> part is the board. Many companies' own careers pages (e.g. coinbase.com/careers) are Greenhouse boards too; their job links carry gh_jid=.
2. Open the actor and click Try for free (or Start).
3. In Greenhouse boards, add one company per line: airbnb, or a URL like https://job-boards.greenhouse.io/discord.
4. Optionally add filters: Title contains (engineer), Title excludes (intern), Location contains (remote, London), Department contains (sales) and Posted within (days).
5. Leave Include salary range on to get published pay ranges (one extra request per job, included in the price).
6. Click Start, then open the Output tab and export as JSON, CSV, Excel or HTML, or read the results through the API.

Input examples

All jobs from one company:

{
    "boards": ["discord"]
}

Several companies, software roles only (the :* prefix syntax used by other job APIs is accepted):

{
    "boards": ["airbnb", "discord", "stripe"],
    "titleSearch": ["Soft:*"]
}

Jobs in London across several companies:

{
    "boards": ["stripe", "datadog", "cloudflare"],
    "locationSearch": ["London, England, United Kingdom"]
}

Engineering jobs posted in the last 7 days, no senior roles:

{
    "boards": ["anthropic", "reddit", "figma"],
    "titleSearch": ["engineer"],
    "titleExclusionSearch": ["senior", "staff"],
    "postedWithinDays": 7
}

Board URLs in the urls format other Greenhouse scrapers use:

{
    "urls": [{ "url": "https://job-boards.greenhouse.io/airbnb" }]
}

Output example

A real row from a test run (descriptions shortened here):

{
  "id": "8175363",
  "title": "Acceleration Programs Intern",
  "organization": "Coinbase",
  "board": "coinbase",
  "url": "https://www.coinbase.com/careers/positions/8175363?gh_jid=8175363",
  "apply_url": "https://www.coinbase.com/careers/positions/8175363?gh_jid=8175363#app",
  "date_posted": "2026-09-08T22:53:27.000Z",
  "date_updated": "2026-10-30T14:53:15.000Z",
  "locations": ["Hybrid - New York, NY", "US - Remote Zone 1 (Job Requisitions Only)"],
  "location": "Hybrid - New York, NY",
  "departments": ["Internships & Emerging Talent Positions"],
  "offices": ["US - Remote Zone 1 (Job Requisitions Only)"],
  "salary_min": 40,
  "salary_max": 40,
  "salary_currency": "USD",
  "salary_title": "Hourly Rate:",
  "requisition_id": "P78056",
  "internal_job_id": "3538143",
  "language": "en",
  "metadata": { "Team": "People Success" },
  "description_text": "Ready to do the most impactful work of your career? At Coinbase, we are uncompromising on our mission to increase economic freedom. …",
  "description_html": "<div class=\"content-intro\"><p>Ready to do the most impactful work of your career? …",
  "source": "greenhouse",
  "scrapedAt": "2026-11-08T23:05:33.276Z"
}

Use cases

• Job boards and aggregators. Backfill a niche job board with fresh listings straight from the companies you cover, with full descriptions and apply links.
• Recruiting and sales intelligence. Watch which companies are hiring for which teams; a burst of sales or engineering roles is a buying or growth signal.
• Salary benchmarking. Collect published pay ranges by title and location from companies that disclose them.
• Job alerts for yourself or your community. Run daily with only-new mode and a title filter, and send new roles to Slack, email or a Discord channel.
• Labour-market research. Track hiring volume, remote share and department mix across a list of companies over time.
• AI agents. Let an assistant answer "what data roles is Stripe hiring for in London?" by calling the actor through MCP.

Run it on a schedule and get only new jobs

1. Save your input as a Task in Apify Console.
2. Open the task's Schedules tab and run it daily (or hourly for fast-moving boards).
3. Turn on Only new jobs ("onlyNew": true). The actor remembers every job it has returned (for 180 days, in a key-value store named greenhouse-jobs-seen in your account) and returns only jobs that are new since the last run, so you pay only for new ones.
4. Add an integration (Slack, Google Sheets, a webhook) so new jobs arrive where you work.

Integrations

API (one call, returns the jobs):

POST https://api.apify.com/v2/acts/daedal_quintuplet~greenhouse-jobs-scraper/run-sync-get-dataset-items?token=YOUR_APIFY_TOKEN
Content-Type: application/json
{"boards": ["airbnb", "stripe"], "titleSearch": ["engineer"]}

Python (pip install apify-client):

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("daedal_quintuplet/greenhouse-jobs-scraper").call(
    run_input={"boards": ["airbnb", "stripe"], "titleSearch": ["engineer"]}
)
for job in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(job["organization"], "|", job["title"], "|", job["location"], "|", job.get("salary_min"))

JavaScript / Node.js (npm install apify-client):

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' });
const run = await client.actor('daedal_quintuplet/greenhouse-jobs-scraper').call({
    boards: ['airbnb', 'stripe'],
    titleSearch: ['engineer'],
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((job) => console.log(job.organization, '|', job.title, '|', job.url));

No-code tools:

• n8n: use the Apify node, choose Run actor, enter daedal_quintuplet/greenhouse-jobs-scraper and your input JSON, then read the dataset items.
• Make: use the Apify app's Run an Actor module, then Get Dataset Items.
• Zapier: use the Apify integration's Run Actor action, or trigger a Zap when a scheduled run finishes.
• Google Sheets, Slack, webhooks: connect them from the actor's Integrations tab in Apify Console.

AI agents (MCP): the actor is available through Apify's MCP server (https://mcp.apify.com). Add daedal_quintuplet/greenhouse-jobs-scraper as a tool and Claude, Cursor or any MCP client can pull jobs on request. Every input field has a plain description and an example so the agent can fill it in.

Pricing

Pay per result: $1.20 per 1,000 jobs ($0.0012 per job). Error rows are free. A 200-job company costs $0.24. Platform usage and salary lookups are included in the price.

Limits and error items

• Only companies that use Greenhouse are covered. Lever, Workday, Ashby and other applicant tracking systems are not.
• The actor returns the jobs that are open right now; closed jobs disappear from the board.
• Salary fields are empty when the company does not publish a pay range.
• Filters match text case-insensitively. A location like New York, New York, United States also matches on the city alone, because boards write locations differently (New York, NY).
• Bad input produces an error row instead of a crash. Examples: {"error": true, "board": "nonexistentboardxyz123", "message": "Greenhouse board \"nonexistentboardxyz123\" was not found. …"}, {"error": true, "board": "discord", "message": "No jobs on \"discord\" matched your filters."} and {"error": true, "board": "webflow", "message": "Board \"webflow\" has no open jobs right now."}. Error rows are never charged; filter them out with error != true.
• If the platform restarts a run (a host migration), the actor resumes where it stopped and does not return or charge the same jobs twice.

FAQ

Do I need a Greenhouse account or API key? No. The actor reads the public job board data that companies publish for applicants.

How do I find a company's board name? Open any job on their careers site. If the URL contains greenhouse.io/<name> the board is <name>. If it contains gh_jid=, the company uses Greenhouse under its own domain; the board name is usually the company name (e.g. coinbase). The actor also accepts full URLs.

Can I search all Greenhouse companies at once? Greenhouse has no public cross-company search, so you list the companies you want. You can list hundreds in one run.

How fresh is the data? Live: each run reads the boards at that moment.

Why do some jobs have two locations? locations combines the location line on the job with the full address of each office it's attached to, so filters and maps work either way.

How many jobs can I get? Every open job on each board. maxItems caps the total (default 1,000, up to 100,000).

Does it collect personal data? No. It returns job postings only.

Related actors

More scrapers from the same developer:

• Google Jobs Scraper: Google Jobs listings for US and UK searches with salary, description and apply links.
• SEEK Australia Job Scraper: job listings from SEEK Australia.
• SEEK New Zealand Job Scraper: job listings from SEEK New Zealand.
• Google Images Scraper: image URLs, sizes and source pages from Google Images searches.
• Google Trends Scraper (all widgets): interest over time, by region, related topics and queries.