Karriere Jobs Scraper

Searching Karriere.at by hand means clicking through page after page and copying each role, company, and salary into a sheet by yourself. This scraper does the clicking for you. Give it a few job titles, optionally a city or two, and it walks the Karriere.at results and hands back every posting as a clean row with the title, employer, location, salary, and contract type already split into fields. It's fast, cheap, and code-free, and you only pay for what you scrape.

What you get

Each posting comes back as one row, grouped into three kinds of data:

• The role — positionTitle, listingUrl, contractType, payDetails, remoteOption, workLocations, postedDate
• The employer — employerName, employerLogo, promotedListing, listingBadges
• Run context — searchTerm, searchArea, collectedAt, and errorMessage if a search could not be completed

Quick start

1. Hit Try for free and type one or more job titles into Search terms (for example projektmanager).
2. Optionally add cities or regions under Search areas to narrow each search; leave it blank to cover all of Austria.
3. Set a Results limit to cap how many postings come back per search.
4. Press Start, then export the rows as JSON, CSV, Excel, or XML.

Use cases

• Recruiters — track which roles competitors are hiring for and where, then pitch candidates faster
• Job seekers — pull every matching opening into one sheet instead of scrolling the site
• Salary research — gather payDetails across a role or city to benchmark pay bands
• Market analysts — measure hiring demand by employer, region, or contract type over time
• Recruitment tech — feed live Karriere.at postings into your own job board or matching tool

Input

Field	Type	Required	Description
searchTerms	array of strings	Yes	Role names or keywords to look up. Add several to run them in one pass. Prefilled with projektmanager.
searchAreas	array of strings	No	Cities or regions to filter each search. Leave empty to search all of Austria.
resultsLimit	integer	No	Most postings to collect per term and area pairing. Default 10.
timeoutSeconds	integer	No	Seconds to wait on each request before it times out. Default 45.

Example input

{
    "searchTerms": ["projektmanager", "data analyst"],
    "searchAreas": ["Graz", "Salzburg"],
    "resultsLimit": 10,
    "timeoutSeconds": 45
}

Output

Each search term runs against each area you supply, or once across Austria when no area is given, paginating automatically up to your limit. Every posting on the results becomes one row. Fields a card does not show come back as null rather than guessed.

Example output

{
    "positionTitle": "Projektmanager (m/w/d)",
    "listingUrl": "https://www.karriere.at/jobs/8123456",
    "employerName": "Alpine Tech GmbH",
    "employerLogo": "https://www.karriere.at/assets/company/alpine-tech-logo.png",
    "promotedListing": false,
    "listingBadges": "Einblicke",
    "workLocations": "Graz",
    "contractType": "Vollzeit",
    "remoteOption": true,
    "payDetails": "ab € 3.500 brutto monatlich",
    "searchTerm": "projektmanager",
    "searchArea": "Graz",
    "postedDate": "vor 2 Tagen",
    "collectedAt": "2026-06-29T12:00:00.000000+00:00",
    "errorMessage": null
}

Output fields

Field	Type	Description
positionTitle	string	Headline of the advertised role
listingUrl	string	Direct link to the posting on Karriere.at
employerName	string	Company that posted the opening
employerLogo	string	Link to the hiring company's logo
promotedListing	boolean	True when the posting is sponsored or boosted
listingBadges	string	Tags or labels on the card, such as Einblicke
workLocations	string	Place or places where the job is based
contractType	string	Working arrangement such as Vollzeit or Teilzeit
remoteOption	boolean	True when home office or remote work is offered
payDetails	string	Salary figure or range as printed on the card
searchTerm	string	Keyword that surfaced this posting
searchArea	string	City or region applied as a filter
postedDate	string	When the listing went live, as shown on the card
collectedAt	string	ISO 8601 timestamp of when the row was captured
errorMessage	string	Reason a search failed; null on success

Tips for best results

• Be specific with search terms. A tight keyword like senior data analyst returns more relevant rows than a broad one like analyst.
• Add areas only when you need them. Each area multiplies the searches, so list a couple of cities rather than a long string of them.
• Start small with resultsLimit. Run 10 first to confirm the output fits your pipeline, then raise it for the full pull.
• Some cards are sparse. payDetails and listingBadges are blank when a posting omits them; the rest of the row still comes through.
• Raise timeoutSeconds if you see timeouts while pulling large result sets.

How can I use Karriere.at job data?

How can I use the Karriere Jobs Scraper to track hiring in Austria? Add the roles you care about to searchTerms, optionally pin a few cities in searchAreas, and run it on a schedule. Each row carries employerName, workLocations, contractType, and postedDate, so you can watch who is hiring, where, and how that shifts week to week.

How can I collect Karriere.at salary data for benchmarking? Pull a single role across several cities and read payDetails alongside workLocations and contractType. Export to CSV or Excel and you have a structured pay dataset to compare bands by region and arrangement.

How can I build a job dataset from Karriere.at for a job board? Feed in the keywords your audience searches, set resultsLimit to the volume you need, and export. Every posting comes back with positionTitle, listingUrl, employerName, and payDetails ready to drop into your own board or matching engine.

Is it legal to scrape data?

Our actors are ethical and do not extract any private user data, such as email addresses or private contact information. They only extract what the user has chosen to share publicly. We therefore believe that our actors, when used for ethical purposes by Apify users, are safe.

However, you should be aware that your results could contain personal data. Personal data is protected by the GDPR in the European Union and by other regulations around the world. You should not scrape personal data unless you have a legitimate reason to do so. If you're unsure whether your reason is legitimate, consult your lawyers.

You can also read Apify's blog post on the legality of web scraping.

Support

Questions, feature requests, or a field you'd like added? Reach out at data.apify@proton.me and we'll get back to you.