Each Greenhouse board belongs to one employer and lives at its own address. Our Greenhouse scraper joins many of them into one table of open roles, departments and pay.
Plans from €169 a month · Free project assessment · Reply within 1 business day
CSV · Excel · JSON · XML · FTP · SFTP · Amazon S3 · Google Cloud
API, JSON feed or CSV, XLSX and JSON files
ScheduleOne-time, monthly, weekly, daily or 3 times a day
Greenhouse pages, filters, fields and a schedule
Built, monitored and repaired by our team
API, JSON feed or CSV, XLSX and JSON files
You send the employers you care about - company names, career site links or Greenhouse board addresses - and we locate each board, whether it sits on job-boards.greenhouse.io, on an older boards.greenhouse.io link, on job-boards.eu.greenhouse.io or inside the company's own career site. We build the crawlers, run them once or on your schedule and repair them when a board changes its layout or moves. Anti-bot handling, pacing and rendering are part of the service.
Every row keeps the board token and the numeric job id, so a role stays traceable across runs even when its title is edited. Field documentation comes with the first delivery, the project starts with a free assessment, and a sample can be ordered first. Plans start from EUR 169 a month, or EUR 199 for a one-time extract.
A Greenhouse board has two layers, and we read both. The board page lists open roles under department headings with a search box and filters; the job page holds the posting itself, the pay block and the application form. The fields:
Only the questions an employer asks are collected, never anything a candidate submits. Names of recruiters, hiring managers or founders that turn up in posting text or a board introduction are personal data and are removed by default.
One Greenhouse board is one employer, so the value sits in the set. We assemble the list of boards with you - from a target account list, a sector or a region - and run them together into one Greenhouse dataset with the employer as a column.
Inside each board we walk every numbered results page and both filters the board offers: Department and, where the employer switches it on, Office. The board's own count of open jobs is stored beside the rows we collected, which shows at a glance whether a run is complete.
History comes from repetition. A daily or weekly run keyed on the job id records when a posting first appeared, when its title, location or pay range changed and when it left the board - the closest public sign of a filled or withdrawn role. Over months that turns into hiring velocity per department and office, and a record of how pay ranges for the same role move. Boards hosted on other applicant tracking systems can join the same table with the same columns.
Greenhouse is an applicant tracking system: employers run hiring in it and publish their openings on a public job board it hosts. The board is the part a candidate sees, and the part we collect. Each employer gets a token in the address - job-boards.greenhouse.io/gitlab, job-boards.greenhouse.io/discord - and each job a numeric id under /jobs/.
One board can surface in several places. Older links on boards.greenhouse.io still open it, some boards sit on job-boards.eu.greenhouse.io, and many larger companies send visitors to their own career site, where the Greenhouse job list is embedded and job links carry a gh_jid parameter. The board interface follows the visitor's browser language, while postings stay in the language the employer wrote them in.
Each employer configures its own board: whether departments nest, whether an Office filter appears, whether the New tag and the job counter show, and what goes into the pay block. Software, fintech, gaming and education companies all hire this way, so two boards rarely look alike even though the structure underneath is shared, and an extractor has to read each one as its owner set it up.
Delivery: CSV, JSON or XLSX files, our API or a JSON feed. MCP server on request.
Full plan detailsA Greenhouse board is the employer's own copy of its openings, so it answers questions that aggregated job sites blur.
Learn how to use web scraping to solve data problems for your organization
Data scraping is the wide term that includes documents, scans and old screens; web scraping is the part that works on websites. We compare sources, daily work, output and cost drivers, give a briefing checklist and walk through two of our projects.
Leveraging advances in technology, the AI-powered web scraper has skyrocketed in demand and is helping to expand capabilities by automating tedious daily tasks and speeding up data collection from thousands of websites several times over.
Web scraping is a method of obtaining web data by extracting it from pages of web resources with the help of a program, that is, in automatic mode. It is used to syntactically convert web pages into more usable forms.
ScrapeIt is a managed web scraping service. We build and run crawlers for job boards, marketplaces and directories and deliver the result as files, a JSON feed or rows in your database. For hiring data we work from the employer list outward: which companies, which boards, how often. Personal data is handled under GDPR, and we do not build profiles of recruiters or candidates.
Still unsure? Write to info@scrapeit.io
Yes. The ScrapeIt Greenhouse API returns the job id, title, department path, location line, pay range blocks and publication date as JSON from an endpoint we host, refreshed on the schedule you set. The same data also comes as CSV or XLSX files, a JSON feed or straight into your database.
Yes. Board pages, job pages and the pay ranges an employer chooses to print are open to any visitor without an account. We collect only publicly available data - everything a visitor can see on a Greenhouse board - and we collect it legally, leaving recruiter names out by default.
Yes. When an employer shows its Greenhouse list inside its own career site, each job link carries a gh_jid value that matches the job id on the hosted board. We collect from whichever address the employer uses and keep that id, so embedded and hosted boards end up with identical rows.
On a large board, most days. New roles appear with the New tag, existing ones get edited titles or pay ranges, and closed roles drop off the board without notice. For hiring signals we usually run daily; for pay benchmarking, weekly is enough.
Yes, wherever the employer publishes them. Each pay block keeps its own heading, minimum, maximum and currency, and the application form is delivered as a list of question labels with a required flag. Answers that candidates submit are never part of the data.
You share your needs, expectations, and desired timeframe. We'll suggest the best solution based on your request and budget.
Our specialists configure the crawlers and extract a sample dataset for your review before proceeding with the full-scale extraction.
Once you approve the sample, we launch the project and start full data collection. We gather, filter, and structure the data for easy use, delivering it on time in your preferred format.
Our team manages ongoing processes, monitors website changes, and supports all data extraction cycles. We can also help integrate data into your systems or create dashboards to simplify analysis.
Tell us which sites, which fields and how often. A couple of lines is enough to start.
Greenhouse data from €169/month. Free project assessment, reply within 1 business day.