Greenhouse Job Scraper — All Jobs by Company, with Salary

Scrape every open job from any Greenhouse job board. Pass a company domain or board slug — get titles, departments, locations, parsed salary and full descriptions in a clean schema.

Input:   ["stripe.com","boards.greenhouse.io/databricks","figma"]
Output:  every open job — normalized, deduplicated, salary parsed

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What you actually get

Real rows from a live run:

Job title	Company	Department	Location	Level	Salary
Account Executive, AI Startups (Hunter)	stripe	Startups - Account Executives (NA)	San Francisco +1	mid	null
Account Executive, Bridge	stripe	Product Sales - MaaS	San Francisco +1	mid	null

Salary reads null when the company doesn't publish one — it is never guessed or filled in.

Straight to a spreadsheet

Export as CSV and nested fields flatten with / — no post-processing:

title,companySlug,department,locations/0,workplaceType,seniority,salary/min,salary/max,salary/currency,postedAt,source
"Account Executive, AI Startups (Hunter)",stripe,Startups - Account Executives (NA),San Francisco,,mid,,,,2026-08-19,greenhouse
"Account Executive, Bridge",stripe,Product Sales - MaaS,San Francisco,,mid,,,,2026-08-19,greenhouse

Full records also carry jobId, employmentType, applyUrl, descriptionText, descriptionHtml, contentHash and scrapedAt. Turn off includeDescription for a smaller, faster payload.

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Input

Accepts any of these, mixed freely:

Company domain (stripe.com), board URL (boards.greenhouse.io/databricks) or bare board slug (figma).

Field	Type	Default	Description
companies	array	—	See above
onlyNewJobs	boolean	false	Return only jobs added or changed since the previous run
trackingKey	string	default	Track multiple company lists independently
includeRemovedJobs	boolean	false	Also emit jobs that disappeared
includeDescription	boolean	true	Include full description text and HTML
maxJobsPerCompany	integer	0	Cap per company (0 = no limit)

You don't need to know the board slug. Pass the company domain and it gets resolved automatically.

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Change tracking — turn it into a hiring monitor

Set onlyNewJobs: true and schedule the Actor. Each run returns only what changed:

• added — posted since the last run
• updated — title, salary, location or description changed
• removed — job closed or pulled

The first run stores a baseline; every run after that is a diff. Useful for sales intelligence (hiring is a buying signal), recruiting, and keeping a job index fresh without re-ingesting everything.

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Output

{
  "jobId": "greenhouse:acme:12345",
  "source": "greenhouse",
  "companySlug": "acme",
  "companyDomain": "acme.com",
  "title": "Senior Backend Engineer",
  "department": "Engineering",
  "team": "Platform",
  "locations": ["New York, NY", "Remote (US)"],
  "workplaceType": "hybrid",
  "employmentType": "FullTime",
  "seniority": "senior",
  "salary": { "min": 180000, "max": 240000, "currency": "USD", "period": "year" },
  "descriptionText": "…",
  "descriptionHtml": "…",
  "applyUrl": "https://…",
  "postedAt": "2026-04-07T17:12:35.753Z",
  "scrapedAt": "2026-08-24T18:03:28.104Z",
  "contentHash": "593a0ec77ef05d3c",
  "changeType": "added"
}

contentHash changes only when meaningful content changes — use it for your own diffing.

seniority is derived from the title: intern, junior, mid, senior, principal, manager, director, executive.

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Salary

Salary ranges are parsed out of the posting text, handling the formats companies actually use. Version numbers, headcounts and date ranges are not mistaken for salary.

$173,000.00 - $259,600.00/yr      →  173000–259600 USD/year
€55k–€70k per year                →  55000–70000 EUR/year
USD 90000 to 120000 annually      →  90000–120000 USD/year
The salary range is $10,000/month →  10000 USD/month

Companies that don't publish salary return salary: null. Nothing is invented.

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Speed

No browser, no proxies — just the public JSON endpoint Greenhouse already serves.

Board	Jobs	Time
Greenhouse / databricks	824	0.5 s
Greenhouse / stripe	577	0.7 s

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Need more than Greenhouse?

ATS Job Scraper covers Greenhouse, Lever, Ashby and Workday in a single run with the same output schema — useful when your company list spans several ATS platforms.

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Notes

• Only public job board data is collected — the same pages any visitor can open. No accounts, no logins, no personal candidate data.
• Companies that can't be matched to a Greenhouse board are skipped with a warning; the rest of the run continues.