Welcome To The Jungle Jobs Scraper

💼 What is Welcome To The Jungle Jobs Scraper?

Welcome To The Jungle Jobs Scraper extracts job ads from Welcome to the Jungle: title, full description, apply link, salary, contract, remote policy, skills, office address with GPS and the employer's profile, for any keyword, city, country, sector or company.

Type a keyword (data engineer), pick a city, or paste a job page or search URL, click Start, and download the jobs in JSON, CSV or Excel. No login, nothing to set up, and it is light: one request per job page, one per 100 job cards — on the Apify platform, with its proxy and the default settings, 100 jobs with their full details took about 1 minute.

📋 What data can you extract from Welcome to the Jungle?

One item per job, 108 fields:

Category	What you get
💼 Job	title, short pitch, full description (text and HTML), required profile, key missions — Chef de projet comptabilité
📄 Contract	contract type and duration, start date, experience and education required — full-time, 6 to 12 months, 4-5 years
🏠 Remote	remote policy — full, partial, occasional or none
💰 Salary	minimum and maximum, currency, period, yearly figure — 45,000-55,000 EUR a year
🎁 Benefits and skills	benefits, skills, tools — days off (RTT), business development, Jira
📍 Location	every office with its full address, ZIP code, city, region, country and GPS — Saint-Herblain, 44800, France
✉️ How to apply	the employer's own application link, the hiring steps, the screening questions of the form
🏢 Company	name, size, creation year, sector, revenue, website, logo, headquarters, gender parity, average age, equality index, labels and commitments
🔗 Company social accounts	LinkedIn, X (Twitter), Facebook, Instagram and YouTube account names
🗂️ Job category	job family, sub-family and role, sectors, in the site's language — Affaires et finance › Comptabilité › Contrôleur de gestion
🕒 Dates and monitoring	publication and update date, republished-ad flag, a fingerprint that changes when the ad changes

Every field, with an example, is listed in the Output section below.

Fields marked (detail) in the Output tab (the full description, applyUrl, skills, tools, officeZipCode, the company profile…) come from the job page and need Extract job details, on by default — at the same price. With it off, the search results alone still fill 68 of the 108 fields. Fields marked (company) need Extract company details.

✅ Why use Welcome To The Jungle Jobs Scraper?

• 🚀 Light: one request per job page, one per 100 job cards — measured on the Apify platform, with its proxy and the default settings: 100 jobs with their full details in about 1 minute, 1,000 in under 9 minutes, and the 3,113 jobs posted in the last day, without details, in 1 minute.
• 🎯 Type the keyword, not a URL: keyword, city, region, country, contract, salary, sector, job family, company or employer label.
• 🧩 Nothing missed, nothing twice: pagination is automatic, a search bigger than the site paginates is read in pieces, and each job is returned once.
• 🗂️ Several searches in one run: keywords × cities, with a cap per search so that one big city cannot eat the whole budget.
• 🔔 Monitoring built in: tick Only new jobs, schedule the Actor, and each run returns (and charges) only what it has never delivered before, plus the ads republished since (flagged isRepost, and skippable).
• 📅 Filters: postedAfter: "7 days", excluded keywords, excluded companies, salary required — a filtered-out job is not saved and never counts in maxItems; postedWithinDays is applied by the site itself, for free.
• 🔌 API, scheduling, monitoring, integrations (Make, Zapier, n8n, Google Sheets…), proxy rotation and JSON/CSV/Excel export via the Apify platform.

🚀 How to scrape Welcome to the Jungle

1. Create a free Apify account.
2. Open Welcome To The Jungle Jobs Scraper and type a Search keyword (e.g. data engineer), then a City if you want one (Paris).
3. Or paste your own Welcome to the Jungle URLs into Start URLs: single job pages, or a search URL (https://www.welcometothejungle.com/fr/jobs?query=..., pagination is automatic).
4. Set Max jobs (100 by default, 0 = no limit) — and Max jobs per search when you run several searches — then click Start.
5. Download the dataset in JSON, CSV, Excel or via API.

💰 How much does it cost to scrape Welcome to the Jungle?

This Actor uses pay per event pricing: $0.40 per 1,000 jobs, full details included — plus $0.0011 per run start at the Actor's default memory (11 cents per 100 runs; the platform counts that event once per gigabyte, so a run you give more memory pays proportionally more). Higher Apify plans pay less per job: $0.38 (Bronze), $0.36 (Silver) and $0.34 (Gold and above) per 1,000. Example: 20,000 jobs ≈ $8; a daily monitor of 300 new jobs ≈ $0.12. The filters the site does not apply itself are checked by the Actor on every job it reads: a job you keep costs its normal price, a job a filter drops costs $0.18 per 1,000 (filter-check: postedAfter / postedBefore, excludeKeywords, excludeCompanies, onlyWithSalary, skipReposts) or $0.18 per 1,000 when a filter that needs the job page drops it (detail-filter-check: onlyWithApplyUrl, onlyWithApplicationQuestions) — $0.175 and $0.171 on Bronze, $0.17 and $0.162 on Silver, $0.165 and $0.153 on Gold. Filtering never costs more than taking every job. Platform usage (compute, proxy) is included in the price.

⚙️ Input

{
    "query": "data engineer",
    "location": "Paris",
    "maxItems": 200,
    "includeDetails": true
}

Several searches, a cap per search, only recent jobs, only the ones not delivered before:

{
    "searchQueries": ["data engineer", "data analyst"],
    "locations": ["Paris", "Lyon"],
    "maxItemsPerQuery": 50,
    "postedAfter": "7 days",
    "onlyNew": true,
    "stateKey": "data-fr"
}

Or with your own URLs:

{
    "startUrls": [
        { "url": "https://www.welcometothejungle.com/fr/jobs?query=data&sortBy=date" },
        { "url": "https://www.welcometothejungle.com/fr/companies/rca/jobs/chef-de-projet" }
    ],
    "maxItems": 500
}

Field	Notes
query, searchQueries	Free-text search, exactly as typed on the site; searchQueries adds more keywords (one search each). Ignored when startUrls is set.
location, locations	Office city, spelled as the site does (Paris, London); locations adds more cities. Every keyword is searched in every city (max 500 searches per run).
startUrls	Search results pages (pagination automatic; the filters of the input that the URL does not set are added; searched on the site of the URL's language — set siteLanguage to the same one) or single job pages.
includeDetails	Read each job page for the full description, the apply link, the skills, the ZIP code and the GPS of the office (default on, same price).
includeCompanyDetails	Read each company page for all its offices and the date its profile last changed, with or without includeDetails (off by default, same price, one more request per company of the run: 61 for the 100 first jobs of the pre-filled search, 28 for the 100 newest jobs of the site, measured on 2026-09-22).
maxItems	Stop after this many jobs for the whole run (0 = unlimited).
maxItemsPerQuery	Cap for EACH search (keyword × city, or search URL). 0 = no per-search cap.
countryCodes, states, districts	Office country (FR, US, GB), region (Ile-de-France) and department (Hauts-de-Seine), as the site spells them.
contractTypes, remoteTypes, educationLevels	full_time, internship, apprenticeship…; fulltime, partial, punctual, no; bac_5, bac_3…
experienceMin, experienceMax	Years of experience the job asks for.
salaryMin, salaryMax, salaryCurrencies	Yearly salary range stated by the employer, and its currency (EUR, USD, GBP). Only about a quarter of the jobs show one.
sectors, professionCategories, professionSubCategories	Company sector (software-1), job family (tech-engineering-3NjUy) and sub-family, by site reference or by name in any of the site languages (Software or Logiciels): a name is turned into its reference.
companies, companyLabels, companyCommitments, companySizeMin, companySizeMax	Only these employers (carrefour), with these labels (happy-trainees) or commitments (social-commitment), of this size.
benefits, jobLanguages, postedWithinDays	Benefits as the site words them in the Site language you pick (RTT / Jour de repos in French), language of the ad (fr, en), jobs published in the last N days.
latitude, longitude, radiusKm	Jobs whose office is within a radius of a point (the three go together).
siteLanguage, sortBy, searchInTitleOnly	Which country site is searched (fr, en, es, cs, sk), relevance or date, and whether the keyword matches the title only.
postedAfter, postedBefore	Publication date range: 2026-09-01, or a period before now (7 days, 2 weeks, 1 month, 24 hours).
excludeKeywords, excludeCompanies	Drop the jobs whose title or summary contains one of these words, or that belong to these companies.
onlyWithSalary, onlyWithApplyUrl, onlyWithApplicationQuestions, skipReposts	Keep only the jobs that state a salary, that link to the employer's own application system, that ask screening questions; drop the ads republished since they were delivered.
onlyNew, stateKey, resetState	Monitoring: only the jobs never delivered under this memory key (a job republished since comes back once, flagged as a repost); resetState forgets the memory.
excludeEmptyFields	Drop the keys that are null or empty from each item (the required ones stay).
Advanced	proxyConfiguration (Apify proxy by default, included in the price; the residential proxy is not available), maxConcurrency, maxRequestsPerMinute (a job page and its company page count as one request), maxRequestRetries, debugLog.

📦 Output

One real item, shortened to its main fields (a run gives all 108):

{
    "id": "f8ee62c7-2fa8-4d09-bc49-2393a8d1d202",
    "reference": "RCA_VA3z7px",
    "url": "https://www.welcometothejungle.com/fr/companies/rca/jobs/chef-de-projet-comptabilite-fiscalite-f-h_saint-herblain_RCA_VA3z7px",
    "title": "CHEF DE PROJET COMPTABILITÉ/FISCALITÉ F/H",
    "summary": "Rejoins RCA, une entreprise dynamique en pleine croissance.",
    "description": "Aujourd'hui, pour évoluer au sein de notre Direction Produit…",
    "keyMissions": [
        "Incarner et porter la vision du produit"
    ],
    "applyUrl": "https://jobs.smartrecruiters.com/RCA1/744000150295830",
    "contractType": "full_time",
    "remote": "partial",
    "experienceLevelMin": 4,
    "salaryMin": null,
    "hasSalary": false,
    "benefits": [
        "Horaires de travail flexibles",
        "Entre 3-4 jours de télétravail"
    ],
    "skillNames": [
        "Développement commercial",
        "Communication"
    ],
    "publishedAt": "2026-09-19T00:01:28.000Z",
    "sectors": [
        {
            "name": "Logiciels",
            "reference": "software-1",
            "parentName": "Tech"
        }
    ],
    "offices": [
        {
            "city": "Saint-Herblain",
            "countryCode": "FR",
            "district": "Loire-Atlantique",
            "state": "Loire Region",
            "address": "Rue Édith Piaf, 44800 Saint-Herblain, France",
            "zipCode": "44800",
            "latitude": 47.22967,
            "longitude": -1.6267
        }
    ],
    "officeCity": "Saint-Herblain",
    "officeZipCode": "44800",
    "latitude": 47.22967,
    "longitude": -1.6267,
    "companyName": "RCA",
    "companySize": 300,
    "companyEqualityIndex": 84,
    "companyJobsCount": 5,
    "contentHash": "2f5a1c9d4b6e8a0f1c3d5e7a9b1c3d5e7a9b1c3d",
    "detailFetched": true,
    "companyDetailFetched": false,
    "searchQuery": "data engineer",
    "scrapedAt": "2026-09-20T12:00:00.000Z"
}

You can download the dataset in various formats such as JSON, HTML, CSV or Excel.

All 108 fields

Fields	What you get
id, reference, slug, wkReference, url	f8ee62c7-…, RCA_VA3z7px, chef-de-projet…, RCA_VA3z7px, https://www.welcometothejungle.com/fr/companies/rca/jobs/chef-de-projet…
title, summary, language	Chef de projet comptabilité, short pitch, fr
description, descriptionHtml, profile, profileHtml, keyMissions	full text and HTML of the ad, the required profile, the list of missions
recruitmentProcess, recruitmentProcessHtml, applyUrl, ats	hiring steps, the employer's own application link, external
contractType, contractDurationMin, contractDurationMax	full_time, 6, 12 (months)
remote, hasRemote	partial, true
experienceLevelMin, experienceLevel, educationLevel	4, 4_TO_5_YEARS, bac_5
salaryMin, salaryMax, salaryCurrency, salaryPeriod, salaryYearlyMin, hasSalary	45000, 55000, EUR, yearly, 45000, true
benefits, skills, skillNames, tools	RTT / Jour de repos, skills with their reference, Développement commercial, Jira
applicationFields, atsQuestions	what the application form asks, the employer's screening questions
publishedAt, publishedAtDate, publishedAtTimestamp, updatedAt, startDate, status, archivedAt, isBoosted	2026-09-19T00:01:28.000Z, 2026-09-19, 1789776088, 2026-09-19T00:01:35.109Z, 2026-10-05 (the start day the employer picked), published, null, false
professionCategory, professionCategoryReference, professionSubCategory, professionSubCategoryReference, professionPivot, professionPivotReference	Affaires et finance, business-finance-1MjQ4, Comptabilité, accounting-5Nzg0, Contrôleur de gestion, management-accountant-5MThl
sectors, sectorNames, sectorReferences	sectors with their parent, Logiciels, software-1
offices, officeCity, officeDistrict, officeState, officeCountry, officeCountryCode, officeAddress, officeZipCode, latitude, longitude	every office (main one first, each with its own address and GPS), then that first one: Saint-Herblain, Loire-Atlantique, Loire Region, France, FR, Rue Édith Piaf, 44800 Saint-Herblain, France, 44800, 47.22967, -1.6267
companyName, companySlug, companyUrl, companyReference, companySummary, companyDescription, companyDescriptionHtml	RCA, rca, its page on the site, 5xRxGwr, what the employer says about itself
companySize, companyCreationYear, companyEqualityIndex, companyLabels, companyCommitments, companySectors	300, 1999, 84, professional-equality, environmental-impact, Software
companyProfileType, companyProfileRanking, companyScore, companyLogoUrl, companyCoverImageUrl, companyIndustry, companyJobsCount	standard, 100, 100, logo and cover, Software, SaaS / Cloud Services, 5
companyWebsiteUrl, companyRevenue, companyTurnover, companyParityMen, companyParityWomen, companyAverageAge, companyHasExternalAts	https://jobs.rca.fr/, 42M€, null, 57, 43, 34, true
companyHeadquarterCity, companyHeadquarterAddress, companyHeadquarterCountryCode	Saint-Herblain, Rue Édith Piaf, FR
companyLinkedin, companyTwitter, companyFacebook, companyInstagram, companyYoutube	the employer's account name on each network, as the site stores it: rca-logiciels, RCA_logiciels, rca.nantes, rca_nantes, @RCA_logiciels (handles, not links)
companyOffices, companyUpdatedAt	every office of the company with its ZIP code and GPS (company)
contentHash, isRepost, detailFetched, companyDetailFetched	2f5a1c… (same hash = nothing changed), false, true, false
searchQuery, searchUrl, scrapedAt	data engineer, the search page it was found on, ISO timestamp

💡 Tips

How to get more results

Set maxItems to 0 and use a broad keyword — or no keyword at all with a country filter. A single search of the site stops at 1,000 results; the Actor gets past that by reading the rest of the search in pieces by publication date, so a country-wide run returns everything the site has. With Sort by on date the jobs still come newest first across the whole run, so a capped run gives you the newest ones, not a random slice.

How to reduce costs

The price is per job, so the levers are maxItems, maxItemsPerQuery, the filters (a filtered-out job costs only its filter check, $0.18 per 1,000 instead of $0.40; postedWithinDays is applied by the site and costs nothing) and onlyNew for recurring runs (you never pay twice for the same job; with skipReposts, not even when the employer republishes it). Turning includeDetails off makes runs faster but does not change the price.

Several searches in one run

Fill searchQueries and / or locations: the Actor runs one search per keyword × city (3 keywords × 4 cities = 12 searches, up to 500 per run). The single query and location fields still work and are added to the lists. A job found by several searches is saved — and charged — once. Set maxItemsPerQuery to give every search its own cap: without it the first searches can use up the whole maxItems budget. You can also paste several search URLs into startUrls: each one is a search of its own, with the same cap.

Monitoring: only the new jobs

Tick Only new jobs (onlyNew) and schedule the Actor. The first run returns everything; each later run skips the jobs already delivered: they are not saved, not charged, and their page is not even read. The memory lives in a named key-value store of your account (welcometothejungle-jobs-scraper-seen, up to 150,000 jobs per key) and is only updated with jobs that really reached the dataset, so a failed run never hides anything. Give each schedule its own stateKey (two schedules sharing a key would hide each other's jobs), and tick resetState once to start over. Searches are then sorted by newest, and a search stops once it meets 100 jobs in a row that you already have (boosted ads pinned at the top are not counted, and neither are ads republished since your last run — the site gives them a new publication date, which puts them back on top). Those republished ads come back once, with isRepost: true; tick skipReposts to drop them instead (their page is not read, and they are not saved; each new job checked costs the filter fee, $0.18 per 1,000).

Filter by publication date

postedAfter and postedBefore take a date (2026-09-01, the whole day is included, UTC) or a period before now (7 days, 2 weeks, 1 month; via the API also 24 hours or a full ISO date-time). The filter reads publishedAt; a job without a publication date is dropped as soon as a date bound is set. Filtered-out jobs are not saved and do not count in maxItems (each job dropped costs the filter fee, see Pricing); the run summary tells how many were filtered. With postedAfter, searches are sorted by newest and stop at the first page that is entirely too old. postedWithinDays does the same job on the site's side: the older ads are never downloaded at all.

🔌 Integrations and API

Call the Actor via the Apify API, the JavaScript or Python clients, or connect it with integrations and webhooks (Make, Zapier, n8n, Google Sheets, Slack, Airtable…). The dataset can be fetched as JSON or CSV from any tool.

🤖 Use with AI agents (MCP)

AI agents (Claude, ChatGPT, Cursor…) can find and run this Actor through the Apify MCP server, billed to their Apify account like any run. It returns one item per Welcome to the Jungle job ad. Actor id: nice_dev/welcometothejungle-jobs-scraper; MCP server with this Actor only: https://mcp.apify.com/?tools=fetch-actor-details,nice_dev/welcometothejungle-jobs-scraper.

Smallest input, for a cheap first call:

{
    "query": "data engineer",
    "maxItems": 10
}

Key output fields: url, title, companyName, contractType, remote, salaryMin, officeCity, publishedAt.

Cost: $0.40 per 1,000 jobs plus $0.0011 per run start at the default memory ($0.34 per 1,000 on the Gold plan); a job a filter drops costs $0.18 per 1,000, see the pricing section above. Cap each call with maxItems and, through the API, with the run option maxTotalChargeUsd.

❓ FAQ

Is it legal to scrape Welcome to the Jungle?

The Actor only reads what Welcome to the Jungle shows publicly to any anonymous visitor. It logs in to nothing. Job ads and company profiles are professional data; the Actor never returns the names of the people behind them. Results may still contain personal data, which is protected by GDPR: do not store it without a legitimate reason. You are responsible for using the data in compliance with Welcome to the Jungle's Terms of Use and applicable law. This Actor is not affiliated with Welcome to the Jungle.

Does it need a login or a proxy?

No login. The proxy is included in the price: leave the default setting (the residential proxy is not available). A request the site turns away is retried at once on a new proxy session (without a proxy, after a pause of 5 seconds, doubled at each retry up to 150 seconds).

Is the data safe to open in Excel or to show on a web page?

Titles and descriptions are the employers' own words, copied as they are. A text can begin with -, +, = or @ (a title such as -20% de turnover): Excel and Google Sheets may read such a cell of a CSV file as a formula or as a number. The Actor leaves the text as it is, so that the JSON and the API give the real value: when you open a CSV, import these columns as text. Every URL field holds an http(s) URL or null, and the …Html fields hold the employer's own HTML, which the Actor does not sanitize: on a web page, escape every field like any text written by a stranger.

Known limitations

• The full description, applyUrl, skills, tools, officeZipCode and the company profile come from the job page: they are null when includeDetails is off.
• With includeDetails off, a job with several offices gets no latitude / longitude: the search results give one pair of coordinates without saying which office it belongs to, and officeCity is then the first office by name, not necessarily the main one. With the details on (default), every office carries its own address and GPS and the main one comes first.
• professionPivot / professionPivotReference (the standard job name the site maps the ad to) come from the search results: they are null for a job URL pasted into startUrls, as are sectors, salaryYearlyMin, hasRemote, isBoosted and companyScore.
• With includeDetails off, about a third of the ads give the required profile as Markdown instead of HTML: profile holds it as text and profileHtml is null.
• companyOffices and companyUpdatedAt need includeCompanyDetails (one more request per company of the run, with or without includeDetails).
• onlyNew remembers job ids, not their content: a job whose description changed is not returned again. contentHash lets you spot such a change on your side.
• Two runs sharing the same stateKey at the same time may both return the same new job.
• A salary is shown on about a quarter of the ads (26 % of the 8 767 jobs counted on the site on 2026-09-22, between 20 % and 41 % depending on the day); salaryMin / salaryMax are null on the others.

A run the platform stops without warning (out of memory, run timeout)

• Resurrect it: it goes on from where it stood at most a minute before the stop. What it had read since is read again, and the jobs already saved are skipped: none is delivered or charged twice, and maxItems still counts them.
• With onlyNew, the memory is saved once a minute: resurrect the stopped run and the jobs it had saved meanwhile join the memory; leave it stopped for good, and the next run may return up to a minute of them once more.

Something doesn't work?

The last line of the log counts the jobs saved, filtered out and no longer on Welcome to the Jungle (taken down while the run was reading them), and the requests that failed after every retry. Those requests and the removed jobs are listed, with the reason, in the FAILED_REQUESTS record of the run's key-value store. A run that saved nothing and had failed requests fails, and its last message gives the cause (a search that does not exist says so, instead of "run it again"). A run that saved some jobs fails too when at least as many requests failed for good as were read (page 1 read, the next pages or the job pages blocked): a green run with a short dataset would hide the outage. One failed request among many is only a warning.

If Welcome to the Jungle changes its pages, you are told instead of paying for blank rows. A results page that counts jobs but gives none the Actor can read is an error (listed in FAILED_REQUESTS), never a quiet "No jobs found". If the first 20 jobs read all lack their title, publication date, company name or — with includeDetails — description, the run saves nothing more, stops and fails, and its last message names the missing field: at most those first jobs are charged. A job that postedAfter / postedBefore drops because it has no date at all counts among those 20.

🛟 Support

Open an issue in the Issues tab with a link to your run: the run log and the FAILED_REQUESTS record of the key-value store show exactly which URLs failed and why.