Eures Job Scraper

What does EURES Job Scraper do?

EURES Job Scraper collects structured job vacancy data from EURES, the European employment portal. Provide an EURES search URL with your keywords and filters, set the result and page limits, and receive job records with titles, employers, locations, dates, categories, language information, and descriptions.

The dataset is useful for recruitment research, hiring intelligence, job aggregation, labor market analysis, employer research, and recurring vacancy monitoring across European countries. Results are available through Apify dataset exports and can be connected to other tools through the Apify API, webhooks, or integrations.

Why use EURES Job Scraper?

• European hiring coverage - Collect vacancies published through EURES and organize them into a consistent dataset.
• Search URL control - Reuse an EURES results URL with its existing keywords, language, sorting, date, occupation, sector, and location filters.
• Useful job context - Capture vacancy identifiers, employers, publication dates, position counts, category codes, schedule codes, language values, and source links.
• Description-ready records - Use description_text for analysis and description_html when the published formatting is useful in a downstream workflow.
• Clean datasets - Duplicate vacancies are skipped and empty values are removed from saved records.
• Repeatable collection - Set a result limit and page limit for testing, scheduled monitoring, or larger research runs.

What data can you extract from EURES?

Field	Type	Description
identifier	String	EURES vacancy identifier.
title	String	Job or vacancy title.
url	String	Direct EURES vacancy detail URL.
company	String	Hiring company or organization.
employer_name	String	Employer name when provided in the vacancy data.
publication_date	String	Date shown as the vacancy publication date.
creation_date	String	Source creation timestamp when available.
last_modification_date	String	Last source update timestamp when available.
number_of_posts	Number	Number of positions advertised.
location_country_codes	String	Comma-separated country codes from the vacancy location data.
location_region_codes	String	Comma-separated regional codes from the vacancy location data.
job_category_codes	String	Comma-separated job category codes.
job_category_primary	String	Primary job category code.
position_schedule_codes	String	Comma-separated schedule codes, such as full-time values.
position_offering_code	String	Position offering code when provided.
available_languages	String	Comma-separated language codes available for the vacancy.
translation_type	String	Translation type from the source data.
translation_language	String	Language code for the selected translation.
translated_title	String	Translated vacancy title when available.
translated_description_text	String	Plain-text translated description when available.
description_html	String	Formatted vacancy description using safe published formatting.
description_text	String	Plain-text vacancy description.
summary	String	Short text summary derived from the description.
eures_flag	Boolean	EURES flag value when present in the source data.
score	Number	Source search score when provided.
source	String	Source label, normally EURES.
source_url	String	EURES data source URL used for the collection.

Some fields are optional because employers, countries, and vacancy types do not all publish the same information.

How to scrape EURES job data

1. Open EURES and create a search with the keywords, country, language, occupation, or other filters you need.
2. Copy the complete EURES search results URL.
3. Paste the URL into the startUrl input.
4. Set results_wanted and max_pages for the size of the run.
5. Start the Actor and review the dataset preview.
6. Export the results as JSON, CSV, Excel, XML, or another Apify-supported format.

The easiest workflow is to prepare the search on EURES first, then pass that URL to the Actor. This keeps the search criteria visible and makes scheduled runs easier to reproduce.

Input Parameters

Parameter	Type	Required	Default	Description
startUrl	String	No	EURES search URL	Complete EURES search results URL. If omitted, the prefilled EURES search URL is used.
results_wanted	Integer	No	20	Maximum number of vacancy records to save. Accepted range: 1 to 10000.
max_pages	Integer	No	10	Maximum number of EURES result pages to process. Accepted range: 1 to 200.
proxyConfiguration	Object	No	{ "useApifyProxy": false }	Optional Apify proxy settings for longer or repeated runs.

Usage Examples

Basic vacancy search

Start with a small EURES search to check the result fields and dataset quality.

{
  "startUrl": "https://europa.eu/eures/portal/jv-se/search?page=1&resultsPerPage=10&orderBy=BEST_MATCH&keywordsEverywhere=admin&lang=en",
  "results_wanted": 20,
  "max_pages": 5
}

Targeted role search

Pass an EURES URL containing a focused title search and collect a larger dataset for recruitment research.

{
  "startUrl": "https://europa.eu/eures/portal/jv-se/search?page=1&resultsPerPage=25&orderBy=BEST_MATCH&keywordsTitle=data%20analyst&lang=en",
  "results_wanted": 100,
  "max_pages": 10
}

Scheduled monitoring run

Use a filtered EURES search URL with a bounded result count and Apify proxy settings for recurring monitoring.

{
  "startUrl": "https://europa.eu/eures/portal/jv-se/search?page=1&resultsPerPage=25&orderBy=PUBLICATION_DATE&publicationPeriod=LAST_7_DAYS&keywordsEverywhere=engineer&lang=en",
  "results_wanted": 200,
  "max_pages": 20,
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": ["RESIDENTIAL"]
  }
}

Sample Output

Each dataset item represents one vacancy. The following example shows the main fields returned by a typical record.

{
  "identifier": "NmU1MjRhN2YtOWUzNy00NjY0LWE1NDAtMTdkM2VmOTA2YzMzIDgx",
  "title": "Site Admin",
  "url": "https://europa.eu/eures/portal/jv-se/jv-details/NmU1MjRhN2YtOWUzNy00NjY0LWE1NDAtMTdkM2VmOTA2YzMzIDgx?lang=en",
  "company": "Enersense Oyj",
  "employer_name": "Enersense Oyj",
  "publication_date": "2026-03-21",
  "creation_date": "2026-03-19T08:02:45.000Z",
  "last_modification_date": "2026-03-21T10:14:09.000Z",
  "number_of_posts": 1,
  "location_country_codes": "FI",
  "location_region_codes": "FI1B",
  "job_category_codes": "3112",
  "job_category_primary": "3112",
  "position_schedule_codes": "FULL_TIME",
  "available_languages": "en,fi",
  "description_html": "Enersense Engineering is currently seeking a Site Admin for a data centre project in Helsinki.",
  "description_text": "Enersense Engineering is currently seeking a Site Admin for a data centre project in Helsinki.",
  "summary": "Enersense Engineering is currently seeking a Site Admin for a data centre project in Helsinki.",
  "eures_flag": true,
  "source": "EURES",
  "source_url": "https://europa.eu/eures/api/jv-searchengine/public/jv-search/search"
}

Tips for best results

• Validate the search first - Run 20 to 50 results before increasing the limits.
• Use a complete URL - Keep the filters in the EURES URL so scheduled runs repeat the same search.
• Choose the right description field - Use description_text for natural-language processing, keyword analysis, and reporting. Use description_html when formatting matters.
• Set a reasonable page limit - A higher max_pages can broaden coverage, while a smaller value keeps test runs shorter.
• Review missing values carefully - Empty fields usually mean the vacancy source did not publish that information.
• Schedule repeat runs - Daily or weekly runs can support hiring trend reports and new-vacancy monitoring.

Integrations and export formats

• Google Sheets - Review vacancies, create hiring trackers, and share reports.
• Airtable - Build a searchable vacancy database for recruitment teams.
• Make or Zapier - Send new dataset items into alerts, CRM records, or internal workflows.
• Webhooks - Notify another service when a run finishes.
• Apify API - Read datasets programmatically and connect the Actor to your own application.

Apify datasets can be downloaded as JSON, CSV, Excel, XML, and other supported formats. JSON is useful for applications and data pipelines, CSV is convenient for spreadsheet analysis, and Excel is suitable for business reporting.

Frequently Asked Questions

Can I use any EURES search URL?

Yes. Copy a public EURES search results URL and provide it as startUrl. The Actor uses the search criteria contained in that URL.

How many vacancies can I collect?

You can request up to 10000 records in one run, subject to the number of matching vacancies and the max_pages limit.

What happens if a vacancy does not include salary or location details?

The record can still be saved. EURES vacancies differ in the information employers publish, so optional fields may be absent.

What is the difference between description_html and description_text?

description_html preserves supported published formatting, while description_text contains a clean plain-text version for analysis and search.

Is proxy configuration required?

No. Short test runs can use the default setting. For larger or repeated runs, you can configure Apify Proxy in proxyConfiguration when needed.

Can I schedule EURES vacancy monitoring?

Yes. Create an Apify schedule for the Actor and reuse the same startUrl, result limit, and page limit on each run.

Is it legal to collect EURES job data?

You are responsible for using the data lawfully. Follow EURES terms, applicable privacy and data-protection rules, and any restrictions that apply to your intended use.

Related Actors

• APEC Jobs Scraper - Collect French executive and professional vacancies from APEC.fr.
• Stepstone Job Scraper - Extract job listings from Stepstone.de for German and European hiring research.
• Learn4Good Job Scraper - Collect worldwide job postings, teaching roles, and career listings from Learn4Good.

Support

For issues, missing fields, or feature requests, use the Issues tab on the Actor page in Apify Console. Include the input URL, run details, and an example of the affected record when reporting a problem.

Legal Notice

This Actor is intended for legitimate collection and analysis of publicly available vacancy information. Users are responsible for complying with EURES terms, applicable laws, privacy requirements, and the rules of any system where the exported data is used.