# Greenhouse Jobs Scraper & API — $1 per 1,000 jobs (`dododata/greenhouse-jobs-scraper`) Actor Every open job from any company's Greenhouse career page as clean JSON — 26 fields, pay ranges as numbers, remote flag, full description. $1 per 1,000 jobs. - **URL**: https://apify.com/dododata/greenhouse-jobs-scraper.md - **Developed by:** [Dodo Data](https://apify.com/dododata) (community) - **Categories:** Jobs, Automation, Lead generation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.70 / 1,000 jobs This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event ## What's an Apify Actor? An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md. ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run. For examples already wired to this Actor's own input schema, see the [API](#api) section below. Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`). # README ## Greenhouse Jobs Scraper & API — $1 per 1,000 jobs Get every open job from any company's **Greenhouse** career page as clean JSON — **26 fields per job, 237 jobs from 2 companies in 5 seconds**: title, department, locations, remote / hybrid flag, pay range as numbers, dates, apply URL and the full description as plain text. Paste career-page URLs or company names. Jobs come straight from the employer's own Greenhouse board: no aggregator, no duplicates, no expired listings. Pay ranges come from Greenhouse's pay-transparency fields, already numeric; descriptions are un-escaped to plain text. ### What you get Ten real rows from the run of 2026-09-18 (descriptions shortened here to 160 characters; the dataset carries them in full): ```json [ { "id": "greenhouse:duolingo:8653419002", "ats": "greenhouse", "company": "duolingo", "company_name": "Duolingo", "title": "Ad Sales Lead, Central", "department": "Business Development", "team": null, "location": "Remote - Illinois", "locations": [ "Remote - Illinois", "Remote" ], "country": null, "workplace_type": "remote", "remote": true, "employment_type": null, "experience_level": null, "salary_min": 140000, "salary_max": 210000, "salary_currency": "USD", "salary_period": "year", "salary_text": "Salary Range:", "posted_at": "2026-07-28T13:47:45.000Z", "updated_at": "2026-08-21T17:02:33.000Z", "requisition_id": "R-01182", "description": "Our mission at Duolingo is to develop the best education in the world and make it universally available. It’s a big mission, and that’s where you come in!\nAt…", "apply_url": "https://careers.duolingo.com/jobs/8653419002?gh_jid=8653419002", "url": "https://careers.duolingo.com/jobs/8653419002?gh_jid=8653419002", "scraped_at": "2026-09-17T20:10:45.949Z" }, { "id": "greenhouse:duolingo:8705196002", "ats": "greenhouse", "company": "duolingo", "company_name": "Duolingo", "title": "Ad Sales Lead - West", "department": "Business", "team": null, "location": "Remote - California", "locations": [ "Remote - California", "Remote" ], "country": null, "workplace_type": "remote", "remote": true, "employment_type": null, "experience_level": null, "salary_min": 152000, "salary_max": 228000, "salary_currency": "USD", "salary_period": "year", "salary_text": "Salary Range:", "posted_at": "2026-08-13T13:22:34.000Z", "updated_at": "2026-09-03T16:23:10.000Z", "requisition_id": "R-01199", "description": "Our mission at Duolingo is to develop the best education in the world and make it universally available. It’s a big mission, and that’s where you come in!\nAt…", "apply_url": "https://careers.duolingo.com/jobs/8705196002?gh_jid=8705196002", "url": "https://careers.duolingo.com/jobs/8705196002?gh_jid=8705196002", "scraped_at": "2026-09-17T20:10:45.950Z" }, { "id": "greenhouse:duolingo:8806187002", "ats": "greenhouse", "company": "duolingo", "company_name": "Duolingo", "title": "Associate Product Manager, Intern", "department": "University", "team": null, "location": "Pittsburgh, PA", "locations": [ "Pittsburgh, PA", "Pittsburgh, Pennsylvania, United States" ], "country": null, "workplace_type": null, "remote": null, "employment_type": null, "experience_level": null, "salary_min": 54, "salary_max": 56, "salary_currency": "USD", "salary_period": "hour", "salary_text": "Hourly Range for this internship is:", "posted_at": "2026-09-15T16:00:00.000Z", "updated_at": "2026-09-15T17:20:27.000Z", "requisition_id": "1267", "description": "Our mission at Duolingo is to develop the best education in the world and make it universally available. It’s a big mission, and that’s where you come in!\nAt…", "apply_url": "https://careers.duolingo.com/jobs/8806187002?gh_jid=8806187002", "url": "https://careers.duolingo.com/jobs/8806187002?gh_jid=8806187002", "scraped_at": "2026-09-17T20:10:45.951Z" }, { "id": "greenhouse:duolingo:8625579002", "ats": "greenhouse", "company": "duolingo", "company_name": "Duolingo", "title": "Consumer Product Lead", "department": "Marketing and Communications", "team": null, "location": "Tokyo, Japan", "locations": [ "Tokyo, Japan", "Remote" ], "country": null, "workplace_type": "remote", "remote": true, "employment_type": null, "experience_level": null, "salary_min": 171780, "salary_max": 257671, "salary_currency": "JPY", "salary_period": "year", "salary_text": "Salary Range:", "posted_at": "2026-07-09T00:07:38.000Z", "updated_at": "2026-07-29T13:16:34.000Z", "requisition_id": "R-01174", "description": "Our mission at Duolingo is to develop the best education in the world and make it universally available. It’s a big mission, and that’s where you come in!\nAt…", "apply_url": "https://careers.duolingo.com/jobs/8625579002?gh_jid=8625579002", "url": "https://careers.duolingo.com/jobs/8625579002?gh_jid=8625579002", "scraped_at": "2026-09-17T20:10:45.953Z" }, { "id": "greenhouse:duolingo:8576434002", "ats": "greenhouse", "company": "duolingo", "company_name": "Duolingo", "title": "Corporate Counsel", "department": "Legal", "team": null, "location": "Pittsburgh, PA", "locations": [ "Pittsburgh, PA", "New York, New York, United States", "Pittsburgh, Pennsylvania, United States" ], "country": null, "workplace_type": null, "remote": null, "employment_type": null, "experience_level": null, "salary_min": 153000, "salary_max": 207000, "salary_currency": "USD", "salary_period": "year", "salary_text": "Salary Range:", "posted_at": "2026-06-03T13:39:17.000Z", "updated_at": "2026-07-28T17:29:31.000Z", "requisition_id": "R-01156", "description": "Our mission at Duolingo is to develop the best education in the world and make it universally available. It’s a big mission, and that’s where you come in!\nAt…", "apply_url": "https://careers.duolingo.com/jobs/8576434002?gh_jid=8576434002", "url": "https://careers.duolingo.com/jobs/8576434002?gh_jid=8576434002", "scraped_at": "2026-09-17T20:10:45.954Z" }, { "id": "greenhouse:figma:5579204004", "ats": "greenhouse", "company": "figma", "company_name": "Figma", "title": "Account Executive, Enterprise (Bengaluru, India)", "department": "Sales", "team": null, "location": "Bengaluru, India", "locations": [ "Bengaluru, India" ], "country": null, "workplace_type": null, "remote": null, "employment_type": null, "experience_level": null, "salary_min": null, "salary_max": null, "salary_currency": null, "salary_period": null, "salary_text": null, "posted_at": "2025-07-22T03:53:16.000Z", "updated_at": "2026-07-22T09:37:08.000Z", "requisition_id": "1759", "description": "Figma is growing our team of passionate creatives and builders on a mission to make design accessible to all. Figma’s platform helps teams bring ideas to lif…", "apply_url": "https://boards.greenhouse.io/figma/jobs/5579204004?gh_jid=5579204004", "url": "https://boards.greenhouse.io/figma/jobs/5579204004?gh_jid=5579204004", "scraped_at": "2026-09-17T20:10:45.569Z" }, { "id": "greenhouse:figma:5783812004", "ats": "greenhouse", "company": "figma", "company_name": "Figma", "title": "Account Executive, Enterprise (Berlin, Germany)", "department": "Sales", "team": null, "location": "Berlin, Germany", "locations": [ "Berlin, Germany", "Berlin, DE" ], "country": null, "workplace_type": null, "remote": null, "employment_type": null, "experience_level": null, "salary_min": null, "salary_max": null, "salary_currency": null, "salary_period": null, "salary_text": null, "posted_at": "2026-02-03T12:13:56.000Z", "updated_at": "2026-07-22T09:37:08.000Z", "requisition_id": "2117", "description": "Figma is growing our team of passionate creatives and builders on a mission to make design accessible to all. Figma’s platform helps teams bring ideas to lif…", "apply_url": "https://boards.greenhouse.io/figma/jobs/5783812004?gh_jid=5783812004", "url": "https://boards.greenhouse.io/figma/jobs/5783812004?gh_jid=5783812004", "scraped_at": "2026-09-17T20:10:45.574Z" }, { "id": "greenhouse:figma:5753209004", "ats": "greenhouse", "company": "figma", "company_name": "Figma", "title": "Account Executive, Enterprise, Mandarin Speaking (Singapore)", "department": "Sales", "team": null, "location": "Singapore", "locations": [ "Singapore", "Singapore, North, Singapore" ], "country": null, "workplace_type": null, "remote": null, "employment_type": null, "experience_level": null, "salary_min": null, "salary_max": null, "salary_currency": null, "salary_period": null, "salary_text": null, "posted_at": "2026-01-13T06:12:25.000Z", "updated_at": "2026-08-25T08:49:20.000Z", "requisition_id": "2070", "description": "Figma is growing our team of passionate creatives and builders on a mission to make design accessible to all. Figma’s platform helps teams bring ideas to lif…", "apply_url": "https://boards.greenhouse.io/figma/jobs/5753209004?gh_jid=5753209004", "url": "https://boards.greenhouse.io/figma/jobs/5753209004?gh_jid=5753209004", "scraped_at": "2026-09-17T20:10:45.577Z" }, { "id": "greenhouse:figma:5428656004", "ats": "greenhouse", "company": "figma", "company_name": "Figma", "title": "Account Executive, Enterprise (Paris, France)", "department": "Sales", "team": null, "location": "Paris, France", "locations": [ "Paris, France", "Paris, Paris, France" ], "country": null, "workplace_type": null, "remote": null, "employment_type": null, "experience_level": null, "salary_min": null, "salary_max": null, "salary_currency": null, "salary_period": null, "salary_text": null, "posted_at": "2025-01-28T13:48:46.000Z", "updated_at": "2026-07-22T09:37:08.000Z", "requisition_id": "1459", "description": "Figma is growing our team of passionate creatives and builders on a mission to make design accessible to all. Figma’s platform helps teams bring ideas to lif…", "apply_url": "https://boards.greenhouse.io/figma/jobs/5428656004?gh_jid=5428656004", "url": "https://boards.greenhouse.io/figma/jobs/5428656004?gh_jid=5428656004", "scraped_at": "2026-09-17T20:10:45.587Z" }, { "id": "greenhouse:figma:5803515004", "ats": "greenhouse", "company": "figma", "company_name": "Figma", "title": "Account Executive, Enterprise (Sydney or Melbourne, Australia)", "department": "Sales", "team": null, "location": "Sydney, Australia • Melbourne, Australia", "locations": [ "Sydney, Australia • Melbourne, Australia", "Sydney, Australia" ], "country": null, "workplace_type": null, "remote": null, "employment_type": null, "experience_level": null, "salary_min": null, "salary_max": null, "salary_currency": null, "salary_period": null, "salary_text": null, "posted_at": "2026-02-18T02:22:34.000Z", "updated_at": "2026-07-22T09:37:08.000Z", "requisition_id": "2147", "description": "Figma is growing our team of passionate creatives and builders on a mission to make design accessible to all. Figma’s platform helps teams bring ideas to lif…", "apply_url": "https://boards.greenhouse.io/figma/jobs/5803515004?gh_jid=5803515004", "url": "https://boards.greenhouse.io/figma/jobs/5803515004?gh_jid=5803515004", "scraped_at": "2026-09-17T20:10:45.591Z" } ] ``` In that run 184 of 237 jobs (78%) carried a published pay range, parsed into `salary_min`, `salary_max`, `salary_currency` and `salary_period`. ### What people use it for - **Track who is hiring, and for what** — e.g. "every new engineering role at my target accounts since yesterday" as a sales or recruiting signal. Set **Posted within (days)** to 1 and schedule it daily. - **Feed a job board, a newsletter or an AI agent with first-party jobs** — e.g. "remote data roles from these 300 companies", without scraping aggregators. - **Benchmark pay and hiring plans** — e.g. "published pay ranges and open headcount by department across my competitors". ### Why not build it yourself Building this yourself: the Greenhouse source, its pagination and quirks, HTML descriptions, pay formats, de-duplication between runs — a day of work, then upkeep each time a field changes. This Actor: **$1.00 per 1,000 jobs**, and when something changes we fix it within 48 hours. Every Apify account includes $5 of free usage a month, so your first 5,000 jobs cost nothing. **Founding price:** $1.00 per 1,000 jobs for the first 100 users. It then rises to $1.50. Users who joined at the founding price keep it. ### Proof | | | |---|---| | Success rate (staging runs on Apify, 17–18 Sept 2026) | 100% — 3 runs, 6 requests, 0 failed attempts | | Last verified against live boards | 2026-09-18 | | Typical run | 235 jobs from 2 companies in 2 to 5 seconds | | Issues answered within | 6 hours | | Changes fixed within | 48 hours | Changelog at the bottom of this page — every fix is dated. ### What we deliberately do not collect - No personal data. Recruiter names, mailboxes and creator fields are never read; e-mail addresses and phone numbers inside descriptions are replaced with `[email removed]` / `[phone removed]`. - Public sources only: what the career page itself shows to any visitor. No logins, no candidate data, nothing behind authentication. - Rate-limited: at most 5 requests a second. - This Actor declares **limited permissions** — it can only write to its own dataset. ### How to run it 1. Click **Run**. The defaults read two sample boards. 2. Replace them with your own **Greenhouse career page URLs** — `https://job-boards.greenhouse.io/duolingo` or `https://boards.greenhouse.io/duolingo` — or list **Companies** by name (`duolingo`). Hundreds of companies per run are fine. 3. Narrow with **Title keywords**, **Locations** (`remote`, `berlin`, `united kingdom`) and **Posted within (days)**. Jobs that do not match are never saved and never charged. 4. Set **Max rows** to cap the run — that is also your spend cap. 5. Download as JSON, CSV or Excel, or call it from the API or from an AI agent through the Apify MCP server. The `id` field is stable, so de-duplicating between runs is one line. A company name that does not exist is reported in the log and skipped; it does not fail the run. Need several systems in one run (Greenhouse, Lever, Ashby, Workday, SmartRecruiters and seven more)? Use the Career Site Jobs Scraper below — same rows, same price. ### Related Actors - [Career Site Jobs Scraper](https://apify.com/dododata/career-site-jobs-scraper) — the same rows from twelve career-page systems in one run - [France Travail Jobs Scraper](https://apify.com/dododata/francetravail-jobs-scraper) — French public-service job offers with salary as numbers ### Input reference | Field | Default | Meaning | |---|---|---| | `startUrls` | sample boards | Greenhouse career-page URLs | | `companies` | none | Company names as they appear in the career-page URL | | `keywords` | none | Keep jobs whose title contains one of these words | | `locations` | none | Keep jobs whose location, country or workplace type contains one of these | | `postedWithinDays` | none | Keep jobs published in the last N days | | `includeDescription` | true | Turn off for lighter rows | | `maxItems` | 500 | Stop after this many rows | | `maxConcurrency` | 5 | Parallel requests | | `useProxy` | true | Use Apify proxy (recommended) | ### Changelog - 2026-09-18 — v0.1 — first release. Verified against live boards on 17 and 18 September 2026. # Actor input Schema ## `startUrls` (type: `array`): Career pages hosted on Greenhouse — e.g. https://job-boards.greenhouse.io/duolingo or https://boards.greenhouse.io/duolingo. Any page of the board works; the company is read from the URL. Leave empty to try the Actor on sample boards. ## `companies` (type: `array`): Alternative to URLs: the company's name on Greenhouse, as it appears in the career-page URL — e.g. duolingo ## `keywords` (type: `array`): Keep only jobs whose title contains one of these words (case and accents ignored), e.g. engineer, data, product. Filtered-out jobs are not saved and not charged. ## `locations` (type: `array`): Keep only jobs whose location, country or workplace type contains one of these, e.g. london, germany, remote. ## `postedWithinDays` (type: `integer`): Keep only jobs first published (or updated, when no publish date exists) in the last N days. Use 1 with a daily schedule to get only new jobs. ## `includeDescription` (type: `boolean`): Turn off for lighter rows when you only need titles, locations and pay. ## `maxItems` (type: `integer`): Stop after this many jobs across all boards. You pay per row, so this is also your budget cap. ## `maxConcurrency` (type: `integer`): Parallel requests. 5 is polite and fast enough for most sites. ## `useProxy` (type: `boolean`): Recommended. Turn off only for testing. ## Actor input object example ```json { "startUrls": [ { "url": "https://job-boards.greenhouse.io/duolingo" }, { "url": "https://job-boards.greenhouse.io/figma" } ], "companies": [], "keywords": [], "locations": [], "includeDescription": true, "maxItems": 500, "maxConcurrency": 5, "useProxy": true } ``` # Actor output Schema ## `results` (type: `string`): No description # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "startUrls": [ { "url": "https://job-boards.greenhouse.io/duolingo" }, { "url": "https://job-boards.greenhouse.io/figma" } ], "companies": [], "keywords": [], "locations": [] }; // Run the Actor and wait for it to finish const run = await client.actor("dododata/greenhouse-jobs-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "startUrls": [ { "url": "https://job-boards.greenhouse.io/duolingo" }, { "url": "https://job-boards.greenhouse.io/figma" }, ], "companies": [], "keywords": [], "locations": [], } # Run the Actor and wait for it to finish run = client.actor("dododata/greenhouse-jobs-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}") for item in client.dataset(run.default_dataset_id).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "startUrls": [ { "url": "https://job-boards.greenhouse.io/duolingo" }, { "url": "https://job-boards.greenhouse.io/figma" } ], "companies": [], "keywords": [], "locations": [] }' | apify call dododata/greenhouse-jobs-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "type": "http", "url": "https://mcp.apify.com/?tools=fetch-actor-details,dododata/greenhouse-jobs-scraper" } } } ``` The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer ` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations). ## OpenAPI specification Download the OpenAPI definition: https://api.apify.com/v2/actors/ch5Uu0d6gyHwj92dg/builds/Ztnah4Lw3S7a63xT9/openapi.json