Welcome to the Jungle Jobs Scraper

Collect current public job listings from Welcome to the Jungle (WTTJ) and turn them into structured recruitment and labor-market data. Search by role, technology, employer or keyword, narrow results by country, city, contract, remote policy and language, and optionally enrich every row from the public job page.

The Actor returns job titles, employers, locations, contract and remote-work metadata, salary fields, publication dates, company size and sector intelligence, descriptions, application links and canonical WTTJ URLs. Results can be exported as JSON, CSV, Excel or XML, scheduled in Apify, or consumed through the API.

What can you use this Actor for?

• Monitor new technology, data, product, sales or operations vacancies.
• Build a structured feed for recruitment research or job-market analysis.
• Track which companies are hiring in a country, city, sector or remote-work segment.
• Compare contract types, disclosed salaries and hiring activity across markets.
• Find growing employers by combining job volume with company size and sector data.
• Power internal dashboards, alerts, spreadsheets, CRMs and data warehouses.
• Create recurring snapshots for trend analysis without manually browsing search pages.

Why scrape Welcome to the Jungle?

Welcome to the Jungle combines job postings with unusually rich public employer profiles. A single search result can include the hiring company, employee count, company-size band, industries, office location, remote policy, contract type and publication time. When detail enrichment is enabled, the Actor also reads the public job page for the full description, application URL, validity date and street-level location metadata when those fields are published.

That combination is useful for more than job hunting. Recruiters can monitor target employers, market researchers can compare hiring patterns, sales teams can identify companies with active expansion signals, and analysts can build repeatable datasets instead of collecting listings manually.

Input

The default run searches for python, fetches job-page details and saves up to 10 jobs. This small default keeps first runs fast and predictable.

Field	Purpose
queries	Roles, employers, skills or free-text terms to search.
locale	Language used for WTTJ links and localized labels.
countryCodes	Optional ISO country filters such as FR, GB, US or DE.
cities	Optional exact city filters such as Paris, London or Berlin.
contractTypes	Filter permanent, temporary, internship, freelance and other contracts.
remotePolicies	Filter fully remote, hybrid, occasional remote, on-site or unknown.
languages	Filter the language of the published job content.
searchTitleOnly	Restrict the keyword match to job titles.
postedWithinDays	Keep jobs published within a recent time window; 0 means any age.
includeDetails	Fetch full descriptions, application URLs and job-page metadata.
maxResultsPerQuery	Maximum unique jobs saved for each query.
maxPagesPerQuery	Safety cap for source pagination.

Example input

{
  "queries": ["python", "data engineer"],
  "locale": "en",
  "countryCodes": ["FR", "GB"],
  "remotePolicies": ["fulltime", "partial"],
  "postedWithinDays": 14,
  "includeDetails": true,
  "maxResultsPerQuery": 25
}

Filters are applied at the source whenever WTTJ exposes them as searchable facets. Posting age is checked against each result's public timestamp. Duplicate jobs shared by multiple queries are saved only once.

Output

Each dataset item is one public job listing. Common fields include:

• reference, object_id, url, apply_url
• title, profile, description_text, description_html, qualifications
• published_at, date_posted, valid_through, language, market
• contract_type, contract_label, remote_policy, department
• experience_level_minimum, education_level, profession, profession_category
• salary_minimum, salary_maximum, salary_yearly_minimum, salary_currency, salary_period
• city, district, region, country, country_code, offices
• latitude, longitude, detail_locations
• company_name, company_url, company_website, company_description
• company_size, company_employee_count, company_logo, company_cover_image
• company_labels, sectors, is_promoted
• source_query, source_search_url, search_rank, scraped_at

Example result

{
  "reference": "PARTO_PqAo88l",
  "url": "https://www.welcometothejungle.com/en/companies/partoo/jobs/lead-developer-python-react-cdi-paris-m-f-d_paris",
  "title": "Lead Developer (Python/React) - CDI - Paris - M/F/D",
  "company_name": "Partoo",
  "company_employee_count": 330,
  "city": "Paris",
  "country": "France",
  "country_code": "FR",
  "contract_type": "FULL_TIME",
  "remote_policy": "partial",
  "published_at": "2026-07-10T15:00:00.000+02:00",
  "apply_url": "https://career.partoo.fr/jobs/...",
  "source_query": "python"
}

Fields remain null when the publisher did not disclose them. The Actor does not invent salaries, experience requirements, contact details or remote-work policies.

Reliable extraction design

The Actor discovers WTTJ's current public search configuration at runtime and uses the same search-only index exposed to visitors by the website. Search pagination is handled with bounded requests and all records are deduplicated by the source job reference. Optional detail requests use browser-compatible HTTP fingerprints and parse structured JobPosting metadata from each public listing page.

Runs fail visibly when no usable records are returned. This prevents an empty dataset from looking like a healthy extraction. The default result limit is intentionally small, while higher limits remain available for production workflows.

Scheduling and integrations

Use an Apify schedule to run the Actor hourly, daily or weekly. A useful monitoring pattern is to search a stable set of roles and countries, keep postedWithinDays narrow, and use reference as the external deduplication key. The dataset API can feed Make, Zapier, n8n, Google Sheets, a database or your own application.

For change detection, store the latest reference values or compare published_at between runs. For employer research, group rows by company_name, company_employee_count, sectors or country_code. For salary analysis, filter out rows without disclosed salary values rather than treating missing values as zero.

Pricing

This Actor uses transparent pay-per-event pricing. A tiny start event covers run initialization, and each unique row pushed to the default dataset is charged as one result event. You are not charged for duplicate records that are discarded before output.

Responsible use

The Actor collects public job and company information. Use the data for legitimate recruitment, research, monitoring and integration workflows. Respect applicable privacy, employment, marketing and database rules. Review a job's canonical WTTJ page before making decisions because listings can change or expire after collection.

FAQ

Does this require a WTTJ login?

No. It reads public search and job-page information without a user account.

Can I search several roles in one run?

Yes. Add multiple values to queries. A job matching more than one query is returned once.

Why is a salary or application URL missing?

Not every employer publishes every field. Keep includeDetails enabled for the richest available output, but undisclosed values remain empty.

Can I collect only recent jobs?

Yes. Set postedWithinDays to a positive number such as 1, 7, 14 or 30.

Can I search only job titles?

Yes. Enable searchTitleOnly to avoid matches that occur only in company or profile text.

How should I avoid duplicates across scheduled runs?

Use reference as the primary key and url as a fallback. Within each run, the Actor already deduplicates by the source reference.

What happens if WTTJ changes?

The Actor refreshes the public search configuration on every run and fails clearly when the source no longer returns usable data. Open an issue from the Actor page if a source change needs attention.

You might also like

• StepStone Scraper for European job-board listings.
• Glassdoor Jobs Scraper for employer and vacancy research.
• Naukri Scraper for India job-market data.
• The Muse Jobs Scraper for public job and company records.

If this Actor saves you time, please leave a review on its Apify Store page. Reviews help prioritize fixes and improvements. For a bug or feature request, open an issue with a small input example and the expected behavior.

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