Welcome to the Jungle Jobs Scraper — Europe Job Listings with Salaries

Get every job listing from Welcome to the Jungle as a clean spreadsheet or JSON feed: title, company, city, remote policy, contract type, salary, full description, benefits and the direct apply link. Search by keyword, city, contract type and remote policy across the French, English, Spanish, Czech and Slovak editions, with no login and no browser needed.

What you get

• Job details: title, contract type (CDI, internship, freelance…), contract length, experience and education level, publication date.
• Salary: minimum, maximum, currency and period (yearly, monthly, daily), whenever the employer publishes it.
• Location: city, country, full address, GPS coordinates, remote policy (full, partial, occasional, none) and every office the job is open in.
• Full description (plain text and HTML), candidate profile, key missions and benefits (e.g. "2-3 days remote", "Meal vouchers").
• Direct apply link to the employer's own applicant tracking system (Lever, Greenhouse, Workday…).
• Company data: name, sector, number of employees, founding year, website, logo and the company's own description.
• Tags: job family, tools (Python, Dataiku, Terraform…) and skills.

Use cases

• Lead generation for recruiters and staffing agencies: find companies that are hiring right now, with their size, sector and website, and pitch them before your competitors do.
• Job aggregators and niche job boards: feed your site with fresh European tech, startup and corporate jobs, de-duplicated and with apply links.
• Salary and market research: compare published salaries by role, city, contract type or experience level; track remote-work adoption across sectors.
• Job-alert bots: run it every morning with "Posted within 1 day" and push new jobs to Slack, Telegram, Discord or email (recipe below).
• AI agents and RAG: clean, structured job descriptions ready to embed in a vector database, or call the scraper as a tool through MCP.
• Monitoring competitors: watch which teams a company is growing, and where.

Sample output

The first 3 items from a run with the default input ("data scientist" in Paris), trimmed to the most useful fields. Every item has ~35 fields; see the full list in the Output tab.

[
  {
    "jobId": "8afd3e0d-c0b8-46ba-a804-49be349798df",
    "url": "https://www.welcometothejungle.com/fr/companies/ekimetrics/jobs/stage-2027-business-data-scientist-marketing-effectivness_paris",
    "title": "Stage 2027 Business Data Scientist - Marketing effectivness",
    "company": {
      "name": "Ekimetrics",
      "sector": "IT / Digital",
      "size": 500,
      "website": "https://www.ekimetrics.com/?language=fr"
    },
    "location": { "city": "Paris", "country": "France", "remote": "partial" },
    "contractType": "internship",
    "salary": { "min": null, "max": null, "currency": null, "period": null },
    "experienceLevel": null,
    "educationLevel": null,
    "publishedAt": "2026-09-25T00:01:43.000Z",
    "descriptionText": "Ekimetrics est un leader mondial de l'efficacité marketing et commerciale et des solutions d'IA à l'échelle. Depuis 2006, nous aidons les en…",
    "benefits": ["Entre 3-4 jours de télétravail", "Team building", "Afterworks, Déjeuners d'équipe, etc."],
    "applyUrl": "https://jobs.lever.co/ekimetrics/8f0d6bb4-903a-4deb-8689-2f72e8b3e171/apply?lever-source%5B%5D=WTTJ",
    "languages": ["fr"],
    "tags": ["Scientifique des données", "Données/Business Intelligence", "Kong", "Azure"]
  },
  {
    "jobId": "001141c5-7d2b-4d51-a289-29ac2e476799",
    "url": "https://www.welcometothejungle.com/fr/companies/aqemia-1/jobs/senior-data-engineer_london_t5m5dsi2",
    "title": "Senior Data Engineer",
    "company": { "name": "Aqemia", "sector": "Logiciels", "size": 71, "website": "https://www.aqemia.com/" },
    "location": { "city": "London", "country": "United Kingdom", "remote": null },
    "contractType": "full_time",
    "salary": { "min": null, "max": null, "currency": null, "period": null },
    "experienceLevel": "5_to_7_years",
    "educationLevel": null,
    "publishedAt": "2026-09-27T00:05:56.000Z",
    "descriptionText": "• As our Senior Data Engineer, you’ll own AQEMIA’s data platform end to end — from ingestion through the pipeline to the trusted, model-read…",
    "benefits": [],
    "applyUrl": "https://jobs.lever.co/aqemia.com/86818f9e-f167-4adb-b689-e5fc82e7b9fd",
    "languages": ["en"],
    "tags": ["Ingénieur de données", "Données/Business Intelligence", "Terraform", "BigQuery"]
  },
  {
    "jobId": "b87aaafb-4f2b-4851-95db-ff6b2d93d99f",
    "url": "https://www.welcometothejungle.com/fr/companies/artelys/jobs/lead-data-scientist-energie-et-prevision-f-h_paris_ARTEL_NwRPbo3",
    "title": "Lead Data Scientist – Energie et Prévision F/H",
    "company": {
      "name": "Artelys",
      "sector": "Ingénieries Spécialisées",
      "size": 135,
      "website": "https://www.artelys.com/fr"
    },
    "location": { "city": "Paris", "country": "France", "remote": null },
    "contractType": "full_time",
    "salary": { "min": null, "max": null, "currency": null, "period": null },
    "experienceLevel": null,
    "educationLevel": null,
    "publishedAt": "2026-09-25T05:30:02.000Z",
    "descriptionText": "Au sein des équipes Optimisation & Data, vous aurez la charge de conduire des travaux d’étude ou d’implémentation opérationnelle de modèles…",
    "benefits": [],
    "applyUrl": "https://taleez.com/apply/lead-data-scientist-energie-et-prevision-f-h-paris-artelys-cdi/applying?utm_source=wttj",
    "languages": ["fr"],
    "tags": ["Scientifique des données", "Données/Business Intelligence", "Python", "Gestion des entretiens"]
  }
]

When the employer publishes a salary, it looks like "salary": { "min": 43550, "max": 53300, "currency": "EUR", "period": "yearly" }. A missing value is always null, never an empty string, so your spreadsheet formulas and filters keep working.

Pricing

You pay only for what you get. There is no monthly fee.

What	Price	When
Run start	$0.01	Once per run
Job scraped	$0.002	Per job delivered to your dataset
Full description (add-on)	$0.001	Per job delivered with its full description (optional, on by default)

Worked example: 1,000 jobs with full descriptions cost $0.01 + 1,000 × $0.002 + 1,000 × $0.001 = $3.01. Without descriptions it's $2.01. A daily alert that finds about 30 new jobs costs around $0.10 per day.

You stay in control of spending. Set Maximum cost per run when you start the actor. When the budget runs out, the scraper stops cleanly and keeps everything scraped so far. If only the base price still fits, the last job is delivered without its description, so you're never charged for the add-on on a job that doesn't include it. The run's STATS record shows "budgetReached": true when this happens.

Input

Field	What it does	Default
Search keywords	Job titles, skills or companies. One search per line; results are combined and de-duplicated.	data scientist
Location	City, region or country as written on the site (Paris, Île-de-France, Spain, FR, Lyon, France). Empty = everywhere.	Paris
Site edition (language)	fr, en, es, cz, sk. Sets the language of benefits, country names and URLs (it does not filter by country).	fr
Contract types	Any of: permanent/full-time, part-time, fixed-term, internship, apprenticeship, freelance, VIE, graduate program, volunteer, other. Empty = all.	all
Remote work	any, fulltime (fully remote), partial (includes occasional remote), none.	any
Maximum jobs	Stop after this many jobs across all keywords.	100
Include full job descriptions	Adds the full description (HTML + text). Charged as the add-on above.	on
Include company website and description	Adds the company website and its own description.	on
Posted within (days)	Only jobs published in the last N days (1 for daily alerts). 0 = any time.	0
Start URLs	Optional Welcome to the Jungle job pages or job-search pages to scrape as well.	none
Proxy configuration	Residential proxies by default (fewest blocks). Falls back to the standard Apify Proxy automatically if residential isn't available.	Residential
Max concurrency / retries	Advanced tuning.	5 / 5

The default input returns results straight away, with zero edits.

How to use it

Apify Console (no code)

Click Start, wait about 30 seconds, then download results as Excel, CSV, JSON or HTML from the Output tab.

API (cURL)

Replace USERNAME with the publisher's Apify username shown in the actor's URL, and YOUR_TOKEN with your Apify API token.

curl -X POST "https://api.apify.com/v2/acts/USERNAME~welcome-to-the-jungle-jobs-scraper/run-sync-get-dataset-items?token=YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"searchQueries":["product manager"],"location":"Lyon","remote":"partial","maxJobs":50}'

Python

from apify_client import ApifyClient

client = ApifyClient("YOUR_TOKEN")
run = client.actor("USERNAME/welcome-to-the-jungle-jobs-scraper").call(run_input={
    "searchQueries": ["data engineer"],
    "location": "Barcelona",
    "country": "es",
    "contractTypes": ["full_time"],
    "maxJobs": 200,
})
for job in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(job["title"], "|", job["company"]["name"], "|", job["salary"])

Node.js

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_TOKEN' });
const run = await client.actor('USERNAME/welcome-to-the-jungle-jobs-scraper').call({
  searchQueries: ['frontend developer', 'React'],
  location: 'Paris',
  postedWithinDays: 7,
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(`${items.length} jobs`, items[0]);

Make (daily job alert → Slack or email)

1. Schedule: a Make scenario that runs every day at 8:00.
2. Apify → Run an Actor: pick this actor, turn Run synchronously on, and use this input: {"searchQueries":["data scientist"],"location":"Paris","postedWithinDays":1,"maxJobs":100}
3. Apify → Get Dataset Items: use the defaultDatasetId from step 2.
4. Iterator over the items, then optionally a Filter (e.g. salary.min is greater than 50000).
5. Slack → Create a Message (or Gmail → Send an Email): {{title}} at {{company.name}} ({{location.city}}): {{url}}.

Because postedWithinDays = 1, each morning you get only the jobs published in the last 24 hours, usually for a few cents.

n8n (same recipe)

1. Schedule Trigger: every day at 08:00.
2. Apify node → Run an Actor and get dataset: actor USERNAME/welcome-to-the-jungle-jobs-scraper, with the same JSON input as above.
3. IF / Filter node: e.g. {{ $json.location.remote }} equals fulltime.
4. Slack / Telegram / Send Email node: message {{ $json.title }} — {{ $json.company.name }} — {{ $json.url }}.

No Apify node available? Use an HTTP Request node with POST to the run-sync-get-dataset-items URL from the cURL example.

MCP (Claude, Cursor and other AI agents)

Add the Apify MCP server with this actor enabled, and your AI assistant can search jobs on demand ("find remote data engineering jobs in Spain posted this week"):

{
  "mcpServers": {
    "apify": {
      "url": "https://mcp.apify.com/?actors=USERNAME/welcome-to-the-jungle-jobs-scraper",
      "headers": { "Authorization": "Bearer YOUR_TOKEN" }
    }
  }
}

Why not LinkedIn?

LinkedIn has more jobs, but scraping it is expensive and fragile:

• Cost: LinkedIn scrapers need residential proxies and often logged-in accounts, so they typically cost several times more per job.
• Blocking and bans: LinkedIn aggressively rate-limits and blocks automated traffic, and accounts used for scraping get restricted, so runs fail unpredictably.
• Data quality: many LinkedIn jobs have no salary, no remote policy and a truncated description behind a login.

Welcome to the Jungle is the go-to board for European startups, scale-ups and employer-branded corporates. Its listings are structured, so salary, remote policy, contract type, education level, benefits and company size come as real fields instead of free text. This scraper uses the same public search the website uses, over plain HTTP, which makes it fast (100 jobs in about 30 seconds), cheap and reliable. Many teams run both: LinkedIn for breadth, Welcome to the Jungle for richer, cheaper European data.

FAQ

Why does a job have "salary": { "min": null, … }? The employer didn't publish a salary. Roughly 15–30% of listings include one, depending on country and role.

Does "Site edition" limit results to that country? No. It only changes the language of translated fields (benefits, country names) and of the job URLs. Use Location to restrict by country, e.g. Spain or ES.

My location returns nothing. The log suggests close matches (e.g. "Did you mean: Paris?"). Use the city, region or country name as it appears on the site, or a 2-letter country code.

How many jobs can I get? Up to 100,000 per run. Beyond 1,000 results for a single keyword, the scraper automatically splits the search by publication date to get past the site's 1,000-results-per-search limit.

Is the data real-time? Yes. Each run queries the live site.

Some jobs have detailsScraped: false. The job's detail page couldn't be fetched after several retries (usually temporary blocking). The job is still delivered with everything available from search results, but without the description, apply link or company website. You're not charged the description add-on for these jobs. The actor uses residential proxies by default to keep this rare. If you changed the proxy to another group, switch back to RESIDENTIAL.

What does experienceLevel / educationLevel mean? They are the site's codes, e.g. less_than_6_months, 5_to_7_years; bac_3 = bachelor's degree, bac_5 = master's degree, phd.

Limitations

• Only publicly listed jobs are collected. Expired or unpublished jobs disappear from results.
• Salary, experience and education are included only when the employer provides them.
• Descriptions are in the language the employer wrote them in (the site does not translate them).
• If the site changes its structure, the scraper may need an update. Issues are usually fixed within a few days. Please report them in the Issues tab.

Legal and responsible use

This actor collects publicly available job listings and company information only. It does not log in, does not collect candidate data, and does not collect data behind a login. Job listings can occasionally contain a recruiter's name or contact details. If you store or process them, you are responsible for doing so lawfully under the GDPR and other applicable laws (legitimate interest, data minimisation, retention limits). You are also responsible for making sure your use complies with Welcome to the Jungle's terms of use and the laws of your jurisdiction. If you're unsure whether your use case is legitimate, consult a lawyer. Please scrape at a reasonable pace and don't republish content in a way that infringes the rights of employers or the site.