XING Jobs Scraper | Every Job, Salaries & Recruiter Contacts

What does XING Jobs Scraper do?

XING Jobs Scraper extracts job listings from xing.com, the professional network for Germany, Austria and Switzerland, and it reads every job in a search, not just the first page or two. XING itself lists at most 1,000 jobs for any one search; this Actor goes past that cap and returns the whole result set. In testing, a nationwide "python" search came back with 4,440 jobs in under a minute. Each job is a clean record with up to 79 fields: the full description, XING's own summary (responsibilities and qualifications), keywords, salary on about 87% of jobs, company size and industry, and the recruiter emails and phones written in the posting. Export to JSON, CSV or Excel, use the API, or hand the data to an AI agent. No code needed.

Give it search terms, cities and any of XING's filters (employment type, career level, 22 disciplines, remote / hybrid / on-site, posted within, salary range, country, industry), or paste XING search and job URLs. Every matching job comes back with its company, location, salary, apply link and full description. The full details are included with every job, so there is no separate enrichment step to switch on and nothing extra per job. Start it with no input at all and it returns the newest jobs on XING.

New to Apify? Sign up free and use the included monthly platform credit to try this Actor. No credit card needed.

Why this scraper

• 📚 Complete searches: big searches are read in full, past the 1,000 jobs XING shows per search.
• 🧠 Full details included: description, XING summary, keywords and contacts come with every job at no extra charge.
• 💶 Honest salary data: salaryType tells a posted salary range apart from XING's salary estimate (min / median / max).
• ⚡ Fast and low-cost: thousands of jobs per minute, so large runs stay cheap.
• ♻️ Cheap to monitor: incremental mode charges only for NEW, UPDATED and REAPPEARED jobs. Unchanged jobs cost nothing.
• 🤖 AI and API-ready: compact output, MCP-friendly, one-click integrations.

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What data can you extract from XING?

Every record carries 79 fields, grouped like this:

Group	What you get
Job	title, url, id, xingId, slug, jobCode, language, postedAt, refreshedAt, validThrough, isPaid, isTopJob
Classification	employmentType, careerLevel, discipline, industry, each with a stable …Code alongside the label, plus workplaceType (remote / hybrid / on-site), remoteOptions, isRemote
Location	location, city, postalCode, street, region (federal state / canton), country, countryCode, locations (every site of a multi-site job)
Salary	salaryMin, salaryMedian, salaryMax, salaryCurrency, salaryPeriod, salaryType (range / fixed / estimate), salaryIsEstimate, salaryText
Description & XING summary	description as plain text, descriptionHtml, descriptionMarkdown, summary, responsibilities[], qualifications[], keywords[], descriptionHeaderImage
Company	company, companyId, companyUrl (XING page), companyLogo, companySize, companyIndustry, companyCity, companyCountry, companyWebsite
Contacts & apply	contactEmail, extractedEmails, extractedPhones, extractedUrls, socialProfiles, applyUrl, applicationType (XING / external / email / message), easyApply, redirectsToExternalSite
Monitoring	changeType, firstSeenAt, lastSeenAt, previousSeenAt, expiredAt, isRepost, repostOfId, repostDetectedAt, contentHash, plus searchKeyword / searchLocation showing which search found the job

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Key features

• 📚 Full-depth search: XING shows no more than 1,000 jobs per search. When a search is bigger, this Actor still returns every matching job, de-duplicated. A nationwide "python" search returned 4,440 jobs in under a minute.
• 🧠 Full details at no extra charge: every job includes the full description (text, HTML and Markdown), XING's summary with responsibilities and qualifications, keywords and the contacts in the posting. You pay the same per job whether details are on or off.
• 💶 Posted salary vs XING estimate, kept apart: about 87% of jobs carry a salary. salaryType and salaryIsEstimate show whether the employer posted a range or XING estimated one (with a median), so the two never get mixed up in your analysis.
• 🎚️ All of XING's filters: employment type, career level, 22 disciplines, workplace (remote / hybrid / on-site), posted within 24 h / 7 d / 30 d, minimum and maximum salary, country (DE / AT / CH) and industry. Jobs you filter out never reach your dataset, so you never pay for them.
• 📍 City + radius search: search one or more cities with a radius from "city only" up to 200 km, or paste any XING search URL with your filters already set.
• 📇 Recruiter contacts for lead generation: emails, phones, URLs and social profiles pulled from the job text, plus the company website. requireContact keeps only the postings that name an email, a phone or both.
• ♻️ Incremental monitoring: schedule it and get only what changed (NEW / UPDATED / REAPPEARED / EXPIRED). Unchanged jobs are not emitted and not charged. Re-posts of the same job under a new ID can be flagged or skipped.
• 🔔 Notifications: Telegram, Slack, Discord or any webhook (n8n / Make / Zapier).
• 🗣️ English or German labels: employment type, career level, discipline and country in either language. Job texts stay exactly as the employer wrote them.
• 🤖 AI-ready: compact and drop-empty output modes keep payloads small for LLMs and MCP.

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🚀 How to scrape XING

1. Open the Actor and enter one or more search terms (e.g. Softwareentwickler), add locations like Berlin or Zürich, or paste a XING search URL.
2. Pick any filters: employment type, career level, discipline, workplace, posted within, salary, country.
3. Set Max results (0 = every matching job).
4. (Optional) Turn on incremental mode and a notification channel, then Schedule it.
5. Click Start, and download the results as JSON, CSV or Excel, or pull them from the API.

No XING account, no login, no cookies. It runs out of the box.

Quick-start example input

{
  "searchTerms": ["Data Engineer"],
  "locations": ["München"],
  "radiusKm": "50",
  "remoteOptions": ["hybrid", "full_remote"],
  "postedWithin": "7d",
  "maxResults": 200
}

This returns up to 200 data engineering jobs within 50 km of Munich posted in the last week, hybrid or fully remote only. Each comes with its salary, company profile, XING summary and full description, ready to drop into a spreadsheet or an outreach list.

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Input

Configure it in the visual editor, no code needed, or pass JSON via the API. 37 inputs are available, grouped exactly as in the editor.

🔎 Search

Field	Type	What it does
searchTerms	array	Job titles, skills or companies, e.g. Softwareentwickler, Marketing Manager, SAP. Each term is its own search. Leave empty to list every job.
locations	array	Cities such as Berlin, München, Wien, Zürich. Every term runs in every location; results are merged and de-duplicated. A country name becomes a country filter.
radiusKm	enum	Site default, city only, 10, 20, 30, 50, 75, 100, 150 or 200 km around each location.
startUrls	array	XING job search URLs (your on-site filters are kept) or single job URLs. Replaces the search terms when given.
maxResults	integer	Cap on jobs across all searches (default 50). 0 = no limit; big searches are read in full.

🎚️ Filters

Several values inside one filter widen the search (OR); different filters narrow it (AND).

Field	Type	What it does
employmentTypes	array	full_time, part_time, freelance, student, temporary, seasonal, volunteer.
careerLevels	array	student_intern, entry_level, professional, manager, executive, senior_executive.
disciplines	array	22 professional fields, e.g. it_software, engineering_technical, sales_commerce, marketing_advertising, finance_accounting, consulting, hr, legal.
remoteOptions	array	full_remote, hybrid, on_site.
postedWithin	enum	any, 24h, 7d, 30d.
salaryMin / salaryMax	integer	Yearly salary bounds in EUR.
countries	array	DE, AT, CH.
industries	array	Keep jobs whose industry (the job's or the company's) contains one of these words, e.g. Banking, Automotive, Pharma.

🎯 Lead generation

Field	Type	What it does
requireContact	enum	off, email, phone, either or both. Keeps only postings that name a recruiter email and/or phone. Skipped jobs are not charged.

📄 Output

Field	Type	What it does
includeDetails	boolean	Full description, XING summary, keywords and contacts (on by default). Turn off for the smallest records.
descriptionFormat	enum	all, text, html or markdown.
descriptionMaxLength	integer	Cut descriptions to this many characters (0 = full length).
language	enum	en or de for labels such as employment type, career level and discipline.
compact	boolean	Core fields only. Ideal for AI agents and MCP clients.
excludeEmptyFields	boolean	Drop null and empty fields for cleaner output.

♻️ Incremental monitoring

Field	Type	What it does
incrementalMode	boolean	Track jobs between runs and tag each with a changeType. Unchanged jobs are skipped and cost nothing.
stateKey	string	Stable name for the tracked search (derived from your settings if blank).
emitUnchanged / emitExpired	boolean	Also emit UNCHANGED jobs, or a record for every job that has disappeared.
skipReposts	boolean	Leave out jobs that are re-posts of one seen before (same title, company and location, new ID).

🔔 Notifications

Credentials are secret inputs: encrypted at rest, masked in the UI and never written to the run log.

Field	Type	What it does
telegramToken + telegramChatId	string	Telegram bot token + chat or channel ID.
slackWebhookUrl / discordWebhookUrl	string	Incoming webhook URL.
webhookUrl + webhookHeaders	string / object	POST the matched jobs as JSON anywhere: n8n, Make, Zapier.
notificationLimit	integer	Jobs listed per message (1–20, default 5).
notifyOnlyChanges	boolean	With incremental mode, alert only on NEW, UPDATED and REAPPEARED jobs.

⚙️ Advanced

Field	Type	What it does
proxyConfiguration	object	Optional. The Actor works without one; turn it on only if your runs are refused.
maxRequestRetries	integer	Retries per failed request (0–10, default 3).
ignoreUrlFailures	boolean	Skip start URLs that can't be read instead of failing the run.

More example inputs

A senior IT recruiting list across Austria and Switzerland, only postings with a recruiter email:

{
  "searchTerms": ["Java", "Cloud Architect"],
  "countries": ["AT", "CH"],
  "careerLevels": ["professional", "manager"],
  "disciplines": ["it_software"],
  "requireContact": "email",
  "maxResults": 0
}

A daily monitor of new finance jobs in Frankfurt with a salary floor, alerting a Slack channel:

{
  "searchTerms": ["Controller"],
  "locations": ["Frankfurt am Main"],
  "radiusKm": "30",
  "salaryMin": 60000,
  "incrementalMode": true,
  "notifyOnlyChanges": true,
  "slackWebhookUrl": "https://hooks.slack.com/services/..."
}

Paste a search you built on XING, or single job URLs:

{
  "startUrls": [
    { "url": "https://www.xing.com/jobs/search?keywords=Projektmanager&location=Hamburg" },
    { "url": "https://www.xing.com/jobs/berlin-software-engineer-158507933" }
  ],
  "descriptionFormat": "markdown"
}

---

Output

Each dataset item is one XING job. Every record carries the core job, company, location and salary fields; Include full details (on by default) adds the description, XING's summary, keywords and the contacts found in the posting. A real record (descriptions shortened):

{
  "id": "158548413",
  "title": "Teamleiter (m/w/d) Unternehmensberatung Versicherungen",
  "url": "https://www.xing.com/jobs/frankfurt-main-teamleiter-unternehmensberatung-versicherungen-158548413",
  "company": "PBMS PersonalBeratung Matthias Schneider",
  "companyUrl": "https://www.xing.com/pages/pbmspersonalberatungmatthiasschneider",
  "companySize": "1-10 employees",
  "companyIndustry": "HR services and consulting",
  "companyWebsite": "https://www.pbms-frankfurt.de/",
  "location": "Frankfurt am Main, Hessen, DE",
  "city": "Frankfurt am Main",
  "region": "Hessen",
  "countryCode": "DE",
  "workplaceType": "hybrid",
  "isRemote": false,
  "employmentType": "Full-time",
  "careerLevel": "Manager/Supervisor",
  "careerLevelCode": "manager",
  "discipline": "Management and corporate development",
  "industry": "Insurance",
  "salaryMin": 120000.0,
  "salaryMax": 180000.0,
  "salaryMedian": null,
  "salaryCurrency": "EUR",
  "salaryPeriod": "year",
  "salaryType": "range",
  "salaryIsEstimate": false,
  "salaryText": "EUR 120,000 – 180,000",
  "postedAt": "2026-10-14T08:15:21Z",
  "validThrough": "2026-11-13T08:18:16Z",
  "applyUrl": "https://www.xing.com/jobs/frankfurt-main-teamleiter-unternehmensberatung-versicherungen-158548413",
  "applicationType": "xing",
  "easyApply": true,
  "language": "de",
  "description": "Über uns\n\nIm Auftrag einer etablierten mittelständischen und auf Finanzdienstleistungen spezialisierten IT- und Managementberatung … suchen wir Sie als\n\nTeamleiter (m/w/d) Unternehmensberatung Versicherungen …",
  "summary": "Eine etablierte IT- und Managementberatung sucht einen Teamleiter (m/w/d) Unternehmensberatung Versicherungen in Frankfurt am Main. Das Unternehmen ist auf Finanzdienstleistungen spezialisiert und befindet sich auf Wachstumskurs.",
  "responsibilities": [
    "Leitung von Projekten in der Unternehmensberatung.",
    "Beratung zu IT- und Prozessfragen.",
    "Führung und Verantwortung im Team."
  ],
  "qualifications": [
    "Langjährige Erfahrung in Unternehmensberatung.",
    "Führungs- und Umsatzverantwortung erforderlich.",
    "Guter Überblick über Versicherungsfragen."
  ],
  "keywords": ["teamleitung", "projektmanagement", "beratung", "versicherung", "prozessoptimierung"],
  "contactEmail": "Bewerbung@pbms-frankfurt.de",
  "extractedEmails": ["Bewerbung@pbms-frankfurt.de"],
  "extractedPhones": ["06196 / 99 848 48"],
  "socialProfiles": { "xing": "https://www.xing.com/pages/pbmspersonalberatungmatthiasschneider" },
  "searchKeyword": "Manager",
  "source": "xing.com",
  "scrapedAt": "2026-10-18T22:38:12.039506+00:00"
}

Descriptions also come as descriptionHtml and descriptionMarkdown. In incremental mode each record also carries changeType (NEW / UPDATED / REAPPEARED / UNCHANGED / EXPIRED) with firstSeenAt, lastSeenAt and the repost fields.

Data fields

• Core: title, url, id, company, location, workplaceType, employmentType, careerLevel, discipline, industry, postedAt, validThrough.
• Salary: salaryMin / salaryMedian / salaryMax, currency, period, salaryType and salaryIsEstimate. A posted range has no median; an XING estimate does.
• Details (with includeDetails): description (text / HTML / Markdown), summary, responsibilities, qualifications, keywords, descriptionHeaderImage.
• Contacts & signals: contactEmail, extractedEmails, extractedPhones, extractedUrls, socialProfiles, easyApply, isTopJob, isPaid.
• Company: companySize, companyIndustry, companyCity, companyCountry, companyWebsite, companyLogo, companyUrl.
• Apply: applyUrl, applicationType, redirectsToExternalSite.

Every field is present in standard mode (missing values are null). Compact mode returns 17 core fields only, for lean AI and MCP payloads; excludeEmptyFields drops empties entirely. The Output tab also ships four ready-made views: Overview, Salaries (min / median / max with posted-vs-estimate), Companies & contacts, and Changes (incremental).

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♻️ How to monitor XING with incremental mode

Schedule the Actor and turn on incremental mode: each run compares against the last and emits only NEW, UPDATED and REAPPEARED jobs, plus EXPIRED ones if you ask for them. Unchanged jobs are recognised and left out, so they are never charged.

	First run (baseline)	Next run (nothing changed)
Jobs checked	all	all
Records emitted & billed	all	none
Alerts sent	all matches	none

Your cost after the baseline scales with how much XING changes, not with how much you watch:

Daily churn	of 1,000 tracked	billable records	you save
5 %	1,000	50	95 %
15 %	1,000	150	85 %
30 %	1,000	300	70 %

Jobs that disappear and come back are tagged REAPPEARED, so a re-opened role isn't mistaken for a new one. With skipReposts, a job re-published under a new ID (same title, company and location) is left out, so it doesn't count as fresh demand.

Setting up scheduled monitoring

1. Configure your search terms, locations and filters.
2. Turn on Incremental mode (leave maxResults at 0 if you want EXPIRED jobs reported).
3. Run it once to seed the baseline.
4. Open the Schedules tab and set a recurring run, e.g. every morning.
5. Add a notification channel with Notify only about changes on.

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🔔 How to set up XING alerts

Get pinged the moment a matching XING job appears. Fill in only the channels you want:

Channel	What to configure
✈️ Telegram	telegramToken (from @BotFather) + telegramChatId
💬 Slack	slackWebhookUrl (Incoming Webhook URL)
🎮 Discord	discordWebhookUrl (channel webhook URL)
🪝 Webhook	webhookUrl receives the matched jobs as structured JSON, ideal for n8n / Make / Zapier

Each message lists up to notificationLimit jobs with title, company, salary and link. Every channel fires independently, so a broken channel can't stop the scrape or the others. Pair incremental mode with notify only about changes to hear only about genuinely new jobs, with no duplicates across runs.

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💡 What can you do with XING data?

Recruiting and sourcing in the DACH market

Agencies and in-house recruiters see which companies are hiring for a role in Germany, Austria or Switzerland right now, at full depth rather than a sample. The career level, discipline and workplace fields let you segment the list in seconds.

Lead generation for staffing and B2B sales

A company with open roles has budget and a need. Combine companySize, companyIndustry and companyWebsite with the recruiter emails and phones in the posting, and use requireContact to keep only reachable leads.

Salary benchmarking

With salary on about 87% of jobs and a clear posted-vs-estimate flag, you can build pay bands by city, career level and discipline. Use the posted ranges for hard evidence and XING's estimates (with median) for wider coverage.

Labour-market and competitor research

Track hiring volume by discipline, region or employer over time. The full-depth read means your counts reflect the real market, not the 1,000-job slice XING shows.

Job alerts and job boards

Feed a niche job board, a Slack channel or a newsletter with fresh DACH roles every day. Incremental mode delivers only new jobs, so nothing is posted twice.

Skills and requirement analysis

The keywords, responsibilities and qualifications arrays turn thousands of German-language postings into structured skill data. This is useful for training programmes, workforce planning and HR tech.

Feed AI agents and LLM pipelines

Compact JSON goes straight into an LLM context, an MCP tool or a vector store. XING's summary plus excludeEmptyFields and compact mode keep token costs low.

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💰 How much does it cost to scrape XING?

This Actor uses Apify's pay-per-event model: a small fee when a run starts, plus a fee for each job in your dataset. See the Actor's Pricing tab for the current numbers. They're rendered live, so this page never goes stale.

The full description, XING summary, keywords and contacts are part of every job. There is no enrichment add-on and no second charge for details. The Actor is lightweight and fast, which is why the per-job fee can sit at the low end of the market. Three things cut your bill further:

• Filters: jobs you filtered out never reach your dataset and are never billed.
• requireContact: postings without the contact you need are skipped and not charged.
• Incremental mode: after the baseline you pay only for what changed (see the table above).

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🔌 Integrations & export

Export to JSON, CSV, Excel or an HTML table, or pull from the REST API and the JavaScript / Python clients. Runs on a schedule, connects to Google Sheets, Slack, Make, Zapier and n8n, and works as an MCP tool for AI agents. Compact mode keeps token usage small.

Also covering the DACH job market: Arbeitsagentur Jobs Scraper for Germany's largest job board, StepStone Job Scraper for DE + AT jobs, and kununu Company Profile Scraper for the employer ratings that pair with XING's company data.

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🔗 Using the API

Run this Actor from your own code. Example with the Apify Python client:

from apify_client import ApifyClient

client = ApifyClient("<YOUR_API_TOKEN>")

run_input = {
    "searchTerms": ["Softwareentwickler"],
    "locations": ["Berlin"],
    "radiusKm": "30",
    "maxResults": 100,
}

run = client.actor("corvuslab/xing-jobs-scraper").call(run_input=run_input)

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item["title"], item["company"], item["salaryText"])

It also works with the JavaScript/TypeScript client, the Apify CLI and the REST API.

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❓ FAQ

Do I need a XING account or login? No. The Actor reads XING's public job listings without an account, cookies or a Premium membership. It runs out of the box.

How many jobs can I get from one XING search? All of them. XING itself shows at most 1,000 jobs for any one search; when a search is bigger, the Actor still returns every matching job, de-duplicated. Set maxResults to 0 for no limit. XING doesn't show a total count for logged-out searches, so the size of your dataset is the real number.

Why do some jobs have a salary and others don't, and what is salaryType? About 87% of jobs carry a salary. Roughly a quarter of all jobs have a range the employer posted (salaryType: "range" or "fixed"); most of the rest carry XING's own salary estimate (salaryType: "estimate", salaryIsEstimate: true), which also fills salaryMedian. The remaining ~13% have neither, so the salary fields are null. Filter on salaryIsEstimate if you only want employer-posted pay.

How many jobs include a recruiter email or phone? About 28% of postings name an email and about 28% a phone number in the job text; the company website is present on about 15%. XING has no structured contact-person field, so names aren't returned. Use requireContact to keep only reachable postings, and skipped jobs aren't charged.

Why is summary (or responsibilities / qualifications) empty on some jobs? These come from XING's own job summary, which XING writes for roughly half of all postings. The full description is present on every job.

Are the job texts in German? Mostly, yes. Around 97% of XING postings are written in German and are returned exactly as published. The language input switches the labels (employment type, career level, discipline, country) between English and German, for example "Full-time" or "Vollzeit".

How should I write locations? Use the city name as XING spells it: München or Munich work, Muenchen does not. A country name such as Österreich or Switzerland becomes a country filter. A place XING doesn't recognise is skipped with a warning in the log instead of quietly searching everywhere.

Why are Austria- or Switzerland-only runs slower? XING's search is Germany-heavy. A country filter on its own means scanning more jobs to find the AT or CH ones. Add a city such as Wien or Zürich for the fastest runs.

Is the salary filter exact? XING applies salaryMin / salaryMax loosely and counts its own estimates too, so you may see jobs just outside your range. The salary fields in each record let you filter precisely afterwards.

Can I get only new jobs on a schedule? Yes. Turn on incremental mode and schedule it; each run emits only NEW, UPDATED and REAPPEARED jobs and can notify your channel. Unchanged jobs cost nothing.

Is it good for AI agents? Yes. Enable compact mode; the output is MCP-friendly and drops empty fields.

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⚖️ Is it legal to scrape XING?

This Actor collects only publicly available job listings, the same ones anyone can see on xing.com without logging in. It does not access member profiles, private messages or anything behind a login. You're responsible for how you use the data, in particular any personal information such as a recruiter's email or phone, and for complying with XING's terms and applicable law, including the GDPR where it applies. Not affiliated with, endorsed by or sponsored by XING or New Work SE.

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