Xing Jobs Scraper

Xing Jobs Scraper

Extract structured job listings from Xing — the leading professional network in the DACH region (Germany, Austria, Switzerland) with over 22 million members. Get 60+ data fields per job including salary, company details, descriptions, and application links.

Search by keyword, location, and discipline — extract titles, salaries, company metadata, full descriptions, and application URLs from Xing job listings. 60+ structured fields per result, ready for analysis or integration.

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Apify Actor: parsebird/xing-jobs-scraper. Scrapes job listings from Xing.com (DACH region). Call via ApifyClient: client.actor("parsebird/xing-jobs-scraper").call(run_input={"keyword": "Data Analyst", "location": "Berlin", "results_wanted": 50, "enrichedScraping": true}). Supports startUrl (direct Xing search URL), keyword, location, discipline filters. enrichedScraping=true (default) fetches detail pages for descriptions, keywords, career level ($8/1000). Set enrichedScraping=false for core fields only ($1.80/1000). Returns 60+ fields per job: job_id, title, company, location, salary, job_type, discipline, remote, date_posted, description_html, description_text, apply_url, keywords, and more. Full API spec: https://apify.com/parsebird/xing-jobs-scraper/api. Get your token: https://console.apify.com/settings/integrations.

What is Xing Jobs Scraper?

Xing Jobs Scraper extracts job listing data from Xing, the dominant professional network in Germany, Austria, and Switzerland. With over 22 million members and nearly one million active job postings, Xing is the primary job board for DACH-region roles that rarely appear on English-language platforms.

This actor queries Xing's internal API to collect structured job data — no browser automation needed, no API key required. It returns 60+ fields per listing including job title, company name, salary range, location details, full HTML and plain-text descriptions, application URLs, and company metadata.

Use the Xing Jobs Scraper as a Xing API alternative to access DACH job market data at scale. Run it on Apify with built-in scheduling, proxy rotation, and export to JSON, CSV, or Excel.

What data can you extract from Xing?

Field	Description
title	Job title
company	Employer name
location	Primary city
salary	Human-readable salary text (e.g. "EUR 47,500 - EUR 55,000")
salary_raw	Structured salary object with currency, min, max, and period
job_type	Employment type (Full-time, Part-time, etc.)
discipline	Professional field (e.g. Project management, IT)
remote	Remote/hybrid/on-site indicator
description_html	Full job description in HTML
description_text	Clean plain-text description
apply_url	Direct application link
date_posted	Post or refresh date (ISO format)
company_size	Company size range
company_industry	Company industry
keywords	Deduplicated job keywords
url	Direct Xing job URL

The full output includes 60+ fields — see the Output example section for the complete schema.

How to scrape Xing jobs

1. Go to the Actor page — Open Xing Jobs Scraper on Apify. Sign up for a free trial if you don't have an account.
2. Enter your search criteria — Type a keyword (e.g. "Software Engineer"), location (e.g. "Berlin"), and optionally a discipline. Or paste a Xing search URL into the Search URL field.
3. Set limits — Choose how many results you want (Max Results) and the maximum pages to process.
4. Run the actor — Click "Start" and wait for the run to complete. Typical runs finish in under a minute.
5. Download your data — Export results as JSON, CSV, or Excel from the Dataset tab. Or access the data via the Apify API.

Python API example

from apify_client import ApifyClient

client = ApifyClient("YOUR_API_TOKEN")

run = client.actor("parsebird/xing-jobs-scraper").call(run_input={
    "keyword": "Data Analyst",
    "location": "Berlin",
    "results_wanted": 50,
})

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(f"{item['title']} at {item['company']} — {item['salary']}")

JavaScript API example

import { ApifyClient } from "apify-client";

const client = new ApifyClient({ token: "YOUR_API_TOKEN" });

const run = await client.actor("parsebird/xing-jobs-scraper").call({
    keyword: "Data Analyst",
    location: "Berlin",
    results_wanted: 50,
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => console.log(`${item.title} at ${item.company}`));

Input parameters

Parameter	Type	Required	Default	Description
startUrl	string	No	—	Direct Xing jobs search URL; the actor derives search filters from it when keyword/location are not passed explicitly
keyword	string	No	—	Job search keyword or role title (e.g. "Data Analyst", "Projektmanager")
location	string	No	—	City or region filter (e.g. "Berlin", "München", "Wien")
discipline	string	No	—	Professional field filter (e.g. "Project management", "IT")
enrichedScraping	boolean	No	true	Fetch detail pages for full descriptions, keywords, career level, discipline, industry, and remote options. Disable for faster, cheaper runs with core fields only
results_wanted	integer	No	20	Maximum number of job records to collect
max_pages	integer	No	20	Maximum number of result pages to process
proxyConfiguration	object	No	Residential	Proxy settings for stable data collection

Output example

{
    "job_id": "148355491.3c4997",
    "slug": "schoenefeld-junior-projektmanager-strategische-unternehmensentwicklung-148355491",
    "title": "(Junior) Projektmanager (m/w/d) Strategische Unternehmensentwicklung",
    "company": "Krieger Gruppe",
    "location": "Schönefeld",
    "salary": "EUR 47,500 - EUR 55,000",
    "job_type": "Full-time",
    "discipline": "Project management",
    "remote": null,
    "job_category": "Furniture and wood products",
    "date_posted": "2025-12-20T17:24:09Z",
    "description_type": "HtmlDescription",
    "description_text": "We are looking for a motivated Junior Project Manager...",
    "apply_url": "https://krieger-gruppe.softgarden.io/job/...",
    "company_size": "501-1,000",
    "company_industry": "Manufacturing",
    "keywords": ["Project management", "Strategy", "Business development"],
    "url": "https://www.xing.com/jobs/schoenefeld-junior-projektmanager-strategische-unternehmensentwicklung-148355491",
    "detail_error": null
}

Each result contains 60+ fields. Download the full dataset in JSON, CSV, or Excel from the Apify Console.

Tips for best results

Start with focused queries

• Use precise keywords to improve relevance — "Machine Learning Engineer" returns more targeted results than "Engineer"
• Add a location to narrow the result set to a specific city or region
• Use the discipline filter to target a specific professional field

Control your dataset size

• Use a smaller results_wanted value (10–20) for quick validation runs
• Increase gradually for production data collection
• Set max_pages to keep run duration predictable

Use reliable proxy settings

• Residential proxies (the default) deliver consistent results from Xing
• Keep the default proxy configuration unless you have specific routing requirements

Prefer direct search URLs for repeatability

• Use startUrl when you want stable, repeatable search filters
• Save proven search URLs for scheduled runs — ideal for daily or weekly job monitoring

Use cases

📊 DACH job market research — Analyze hiring trends, salary ranges, and demand for specific roles across Germany, Austria, and Switzerland.

🏢 Competitive intelligence — Monitor competitor hiring activity, open headcount, and the professional disciplines they invest in.

🔍 Talent acquisition — Build automated pipelines that surface new Xing job openings matching your criteria daily.

💰 Salary benchmarking — Collect structured salary data across roles, locations, and seniority levels in the DACH region for budgeting or negotiation.

📈 Academic research — Create datasets for labor economics, workforce mobility, or skills-gap analysis in German-speaking markets.

🔗 Lead generation — Identify companies that are actively hiring and use the company data for targeted outreach.

How it works

1. Input parsing — The actor reads your keyword, location, discipline, or startUrl parameters. If a search URL is provided, filters are extracted from the URL automatically.
2. Search API — Queries Xing's internal API with the configured filters. The API returns up to 20 jobs per page with core fields (title, company, location, salary, employment type).
3. Pagination — Walks through result pages until results_wanted is reached or no more results are available. Pages are capped by the max_pages setting.
4. Detail enrichment (enriched mode only) — When enrichedScraping is enabled (the default), the actor fetches each job's full detail page to add descriptions, keywords, career level, discipline, industry, and remote options. Detail requests run concurrently for speed. Disable this for faster, cheaper runs that return core listing fields only.
5. Output — All results are pushed to the Apify dataset. Download as JSON, CSV, or Excel, or access programmatically via the Apify API.

How much does it cost to scrape Xing jobs?

Mode	Event	Price per event	Price per 1,000
Enriched (default)	enriched-job-scraped	$0.008	$8.00
Normal	job-scraped	$0.0018	$1.80

Enriched scraping (default) fetches each job's detail page to extract full descriptions, keywords, career level, discipline, industry, and remote options. Normal scraping returns core listing fields only (title, company, location, salary, job type, apply URL) and is faster and cheaper.

Toggle the Enriched Scraping input to switch between modes. Platform compute costs are included — you only pay per result.

What does a typical run cost? A run collecting 100 enriched jobs costs $0.80. The same run in normal mode costs $0.18. Apify's free trial includes $5 in platform credits, enough to scrape thousands of Xing job listings.

Can I control costs? Yes — set results_wanted to limit how many jobs are collected per run. Disable Enriched Scraping when you only need core listing fields. Start with 20 results to validate your search, then scale up.

FAQ

How fresh is the data? The Xing Jobs Scraper fetches live data directly from Xing's API on every run. Results reflect what is currently published on the platform.

Can I schedule recurring runs? Yes. Use Apify Schedules to run the scraper daily, weekly, or at any custom interval. Combine with Apify Integrations to send results to Google Sheets, Slack, Zapier, Make, or your own webhook.

Can I access the data via API? Yes. Use the Apify API or the official Python and JavaScript clients to run the actor and retrieve results programmatically. See the code examples above.

What export formats are supported? JSON, CSV, Excel (XLSX), XML, and HTML. Download from the Apify Console or retrieve via API.

Does it work without a Xing account? Yes. The actor accesses publicly available job listings. No Xing login or API key is required.

What if I get empty results? Check that your keyword and location match Xing's own search behavior. Try running the same search on xing.com/jobs first to confirm results exist. Broader keywords and fewer filters produce more results.

What does detail_error mean? If the actor cannot fetch the full detail page for a specific job (e.g. the listing was removed between search and detail fetch), it sets detail_error with a reason. Core fields from the search results are still included.

Where can I report issues? Use the Issues tab on the actor page. We respond promptly.

Is it legal to scrape Xing?

This actor accesses only publicly available job listing data from Xing. It does not bypass login walls, access private profiles, or collect personal user data. The data collected consists of job postings that companies have intentionally made public for recruitment purposes. Users are responsible for ensuring their use of scraped data complies with applicable laws, the GDPR, and Xing's Terms of Service. For more information, see Apify's guide on web scraping legality.

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