Greenhouse Jobs Scraper - Job Board API to CSV & JSON

SOURCE COVERAGE & PRACTICAL LIMITS

Full product guide

Documentation captured from build 1.0.7. Example outputs retain their original sample context; they are not live results.

Greenhouse jobs, with readable details

Create a job-posting feed for recruiting, aggregation or employer research from public Greenhouse boards. Each saved row preserves the source posting identity and optional clean-text description.

Open this Actor in Console · First run · Results · Cost · Full guide

Try this Actor

1. Choose a small scope. Start with one documented board token, such as figma, instead of the full prefilled list. Review the per-board posting cap and leave new-postings-only mode off for your first snapshot.
2. Run and review. Open the dataset for job rows and the run's key-value-store SUMMARY for board failures, posting counts and department/office breakdowns.
3. Use the results. Export CSV for flat posting columns or JSON for pipeline use. Keep the board token, job ID and posting link for reconciliation across runs.

Read this before using the data: This Actor covers Greenhouse only. Its remote flag is inferred from location text, and pay mentioned in descriptions is not parsed into structured salary fields. A capped or failed check cannot establish that an omitted job closed.

Result preview

The dataset view highlights these columns:

• Company · company
• Job title · title
• Department · department
• Office · office
• Location · location
• Remote inferred from location · remote

Use the original source links and the field definitions below when interpreting the results. CSV works well for flat columns; JSON preserves nested values.

Usage and pricing

Base result rate on the FREE tier: $1 per 1,000 results. The Pricing tab shows your plan's result rate and any Actor Start charge. Set a small result limit for the first run; the requested limit is not a guarantee of that many results.

Full guide

Scrape live job postings from any Greenhouse job board and get them back as flat CSV, JSON or Excel rows. Give it a board token (figma) or a board URL (https://job-boards.greenhouse.io/figma) and this Greenhouse scraper returns every public opening on that board: job title, department, office, location, a remote flag, the posting URL, and the full job description converted from Greenhouse's HTML into clean plain text, plus a short excerpt for quick scanning.

Built for recruiters, sourcers, job-board operators, ATS data pipelines and anyone tracking hiring at a list of companies. It reads Greenhouse's public job-board API, so there is no API key, no login and no Greenhouse account involved. Pass one company or a hundred.

This Actor covers Greenhouse only. That is deliberate - it is built as a dedicated, well-documented option for Greenhouse boards rather than a thin wrapper over many platforms. A company that is not on Greenhouse cannot be scraped here; see the FAQ for what to use instead.

What you get

One row per public job posting.

A SUMMARY record is written to the run's key-value store with the boards that succeeded, the boards that failed and why, the total postings seen per run, and department and office breakdowns (the 25 most common departments and the 25 most common offices across everything saved, with counts).

Input

Example output

A real row from a default run (description truncated here for readability):

{
  "company": "Dropbox",
  "boardToken": "dropbox",
  "jobId": "8220580",
  "title": "Product Manager",
  "department": "Prod - DocSend (Sub Team)",
  "office": "Canada; Mexico; US",
  "location": "Remote - Mexico",
  "remote": true,
  "firstPublishedAt": "2026-09-23T19:29:17.000Z",
  "updatedAt": "2026-09-23T19:59:04.000Z",
  "absoluteUrl": "https://jobs.dropbox.com/listing/8220580?gh_jid=8220580",
  "contentText": "Role Description\nDocSend is expanding from a virtual data room solution into a deal execution platform. ...",
  "contentExcerpt": "Role Description DocSend is expanding from a virtual data room solution into a deal execution platform. ...",
  "scrapedAt": "2026-09-24T00:52:59.742Z"
}

FAQ

Where do I find a company's board token? Open the company's Greenhouse board in a browser. The token is the path segment: https://job-boards.greenhouse.io/figma and https://boards.greenhouse.io/figma both give figma. You can paste the whole URL into boards and the Actor will parse it. A token with no board returns HTTP 404 and is reported for that board only - the rest of the run continues.

Does it also cover Lever, Ashby, Workday or SmartRecruiters? No. This Actor talks to Greenhouse and nothing else, and a company that is not on Greenhouse will 404 here no matter how the token is spelled. Thumbtack is a good example: it is often assumed to be on Greenhouse, but its public board runs on Ashby (checked 2026-09-23), so it cannot be scraped with this Actor - the run log says so explicitly when you pass thumbtack. For multi-platform coverage, use our ATS Job Postings Scraper, which covers twelve supported ATS platforms, including Greenhouse, Lever, Ashby, Recruitee and Workable. SmartRecruiters is not supported. For Thumbtack specifically, run that Actor with companies: ["thumbtack"] - it detects the Ashby board on its own (verified 2026-09-23: 47 open roles returned).

What exactly does "only postings new since the last run" do? With the option on, the Actor records successfully saved job IDs in the named key-value store greenhouse-jobs-baseline, keyed by board (and platform where applicable). The first run has no baseline and returns matching postings up to your result and charge limits. Later runs return IDs not already saved. Prior seen IDs are retained; newly discovered jobs excluded by filters, result caps, or the charge limit are not marked seen and remain eligible for a later run. A run with nothing new succeeds with an empty dataset and a warning. The baseline is written only while this option is enabled. Runs watching the same board share its baseline, so use one schedule per board and avoid concurrent runs against that baseline.

Is the description really plain text? Yes. Greenhouse returns descriptions as HTML-escaped markup, and parts of it are escaped twice (  in the raw payload), which is why naive scrapers leave   and & scattered through the text. This Actor decodes repeatedly until the string stops changing, then strips the tags and normalizes the whitespace. On a 360-posting sample run, 0 rows contained leftover HTML tags or HTML entities.

Why is there no salary field? Because Greenhouse's public board API does not return a structured salary. Pay ranges show up inside the description when the employer includes them, so they are in contentText - searchable, but not parsed into a number. No made-up column.

How fast is it? Greenhouse returns an entire board in a single response with no pagination, so cost per board is one request. Measured locally on 2026-09-23, end to end including writing the rows: a default run (3 boards, 360 postings, full descriptions) took about 2.3 seconds; 10 large boards totalling 3,056 postings with full descriptions took about 15 seconds. Platform runs add the time to write results over Apify Storage, so expect somewhat more there. Large runs are bounded by maxRunSeconds, not by the number of requests.

Data source, access and limits

• Source: the public Greenhouse job-board API, https://boards-api.greenhouse.io/v1/boards/{board_token}/jobs?content=true. No key, no login, no Greenhouse account, no cookies. Only postings the employer has published publicly on their own board.

• content=true is always requested, because Greenhouse returns the departments and offices arrays only on that endpoint (verified: without it, neither is present in the response). includeContent controls whether the description text is written to the output, not whether it is fetched.

• remote is inferred, not reported. Greenhouse has no remote field. This Actor marks a row remote when the employer's location text contains remote/distributed/work-from-home/anywhere/virtual. A role described as remote only in the body text will read false.

• Everything else is passed through as published. Titles, departments, offices, locations and timestamps come from the employer's own Greenhouse data, including its inconsistencies - department names are whatever each company set up.

• No candidate or application data is extracted. Every row describes a job posting, not a person: there is no recruiter name, email or phone field, and none is inferred. contentText is the employer's own published description reproduced as text, so if an employer wrote a contact address into its posting it stays there - on the 360-row default sample that was one corporate accommodations alias and nothing else. Nothing is collected from candidates or applications.

• Failures are explicit. Boards that 404 or error are named in the log and in SUMMARY, and the run still saves everything from the boards that worked. If every board fails, the run fails with a message naming the likely cause instead of returning an empty dataset that looks like "no jobs".

• Billing: this Actor is billed per result on Apify - the current rate is on the Pricing tab of this Actor's page. There is nothing else to buy; the data source itself is free and keyless.

• Not affiliated with Greenhouse Software, Inc. Greenhouse is a trademark of its owner; this Actor is an independent tool that reads publicly available job-board data.

Saved rows and run charge limits

The Actor writes results one at a time and stops when Apify reports the run charge limit. SUMMARY.stoppedOnChargeLimit distinguishes that stop from an empty source. Saved-row counts include only rows accepted by the dataset. For change detection, prior seen IDs are retained and newly discovered IDs enter the baseline only after their row is saved; rows excluded by a result or charge cap remain eligible for a later run. Avoid concurrent monitor runs sharing the same named baseline store.

Help with your run

Open the Issues tab on this Actor with the run URL, the input field that caused trouble and what you expected to receive. Remove API keys and private information before posting.

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Source record quality

A posting needs a usable source ID and title before it can be saved. Identical duplicate entries in a board response are saved once; conflicting entries with the same ID are reported as a source failure. Confirmed empty boards and filters matching nothing produce a warning and an empty dataset. Failed checks remain visible in SUMMARY, including when no result could be saved.

Understand your run

Open Run report in the run’s Output tab for saved-record counts, reported source issues and limits, and suggested next steps. Use CSV export to take the saved results into a spreadsheet. The existing JSON results and detailed machine-readable summary remain available.

The report reflects this run’s recorded coverage. A successful run or a saved result does not establish that every possible source record was collected.