How to scrape HR and workforce data from Greenhouse using the Minexa.ai extension

A Greenhouse job board page looks clean in a browser. Open the raw source and it is a different story: nested divs, dynamic class names, carousel wrappers, and image paths buried inside attributes. Getting that into a spreadsheet manually takes far longer than it should.

This guide shows how to go from that raw page to a structured, exportable dataset using Minexa.ai, a Chrome extension that detects and extracts data from any web page without requiring any code.

What the page looks like before extraction

The Greenhouse job board at job-boards.greenhouse.io presents job-related content in a carousel-style layout. Each listing row carries a title, a content summary, an image, a topic category label, and a set of related links. None of that is immediately usable in its web form. The image paths are resolved URLs buried in attributes. The category labels are plain text nodes inside deeply nested elements. The carousel identifiers are class strings attached to each slide wrapper.

After running Minexa.ai on this page, all of that becomes a clean table: one row per listing, one column per field, ready to export.

Watch the full extraction

https://www.youtube.com/watch?v=DGYdGk3PMX0

How to set up the scraper step by step

Start by opening the Minexa.ai home page. The extension loads in your browser and is ready to use on any tab.

Navigate to the Greenhouse job board page you want to extract. Once the page has fully loaded, the extension is ready to detect its structure.

Open the extension popup. You will see a button confirming you are on the right page. Click it to proceed.

Minexa.ai will detect the pagination logic on the page and show you what it found. Review the detected pagination and click Continue.

At this point you can choose to scrape just the list on this page, or go deeper and also extract the detail page behind each listing link. For most HR research workflows, scraping the list plus linked details gives you the fullest dataset in a single run.

Select simple scraping mode unless you need custom click sequences or multi-step interactions. For this Greenhouse page, simple mode captures everything needed.

Minexa.ai automatically highlights the full data container on the page. You do not need to click individual fields. The extension identifies the repeating pattern and selects the correct wrapper.

After confirming the container, all extracted data points appear with navigation controls to review each column. This is where you see exactly what fields were found before running the full job.

The extension also shows you the API request and a ready-to-use Python code sample if you want to call the scraper programmatically later.

A summary screen shows the completed configuration. From here you can connect to Google Sheets or set up a recurring schedule so the job runs automatically at whatever interval suits your workflow.

What the structured output looks like

Here is a sample of what Minexa.ai returns from the Greenhouse page. Each row represents one listing, with all fields cleanly separated:

[
 {
 "article_title": "Ryczalt za uzywanie samochodu sluzbowego do celow prywatnych",
 "article_content": "Samochod sluzbowy, ktory moze byc wykorzystywany do celow prywatnych pracownika, to atrakcyjny benefit pozaplacowy.",
 "image_source_url": "https://zarobki.pracuj.pl/media/cache/resolve/article_medium/rc/GpUm78pB/ryczalt.jpg",
 "topic_category": "Zarobki i finanse",
 "slider_class": "swiper-slide swiper-slide-active"
 },
 {
 "article_title": "Jak negocjowac wynagrodzenie w pracy?",
 "article_content": "Strategia negocjacji wynagrodzenia wymaga znajomosci wlasnych oczekiwan finansowych i stawek obowiazujacych w danej branzy.",
 "image_source_url": "https://zarobki.pracuj.pl/media/cache/resolve/article_medium/rc/mjuaXsfx/jak-negocjowac.jpg",
 "topic_category": "Zarobki i finanse",
 "slider_class": "swiper-slide"
 }
]

The slider_class field captures the DOM carousel identifier for each listing row, which is useful for filtering active slides from queued ones. The topic_category field groups listings by subject area, making it straightforward to segment results downstream. The image_source_url field returns the fully resolved image path, not a relative reference.

Once the job runs, data exports to Excel, Google Sheets, or JSON in one click.

Install the Minexa.ai Chrome extension and run your first Greenhouse extraction today.

For more on scraping HR and workforce data from other platforms, see the guide on how to scrape HR and workforce data from Cutshort.