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Willhaben.at Jobs Scraper: Extract Austrian Employment Data Efficiently

Introduction: Why Scrape Willhaben.at Jobs?

Willhaben is Austria's largest digital marketplace and one of the most visited websites in the country, attracting millions of unique users monthly. The platform's jobs section hosts thousands of active employment opportunities across various industries, making it a goldmine for recruitment professionals, HR analysts, market researchers, and business intelligence teams.

With over 400,000 unique users accessing willhaben jobs monthly, the platform represents a comprehensive snapshot of Austria's employment market. However, manually collecting and analyzing this data is time-consuming and impractical. This is where automated job scraping becomes invaluable—enabling professionals to extract, analyze, and leverage employment data at scale for informed decision-making.

Overview: What is the Willhaben.at Jobs Scraper?

The Willhaben.at Jobs Scraper is a specialized data extraction tool designed to automate the collection of job listings from willhaben.at's employment section. This scraper navigates through job search results pages, extracts comprehensive job information, and delivers structured data ready for analysis or integration into your systems.

Key Capabilities

This scraper offers several powerful features that make it essential for employment data collection:

• Multi-URL Processing: Extract jobs from multiple search queries simultaneously, allowing you to gather data across different job categories, locations, or keywords in a single run
• Comprehensive Data Extraction: Captures all critical job information including titles, descriptions, company details, locations, salary ranges, employment types, and metadata
• Residential Proxy Support: Built-in proxy configuration ensures reliable data collection without triggering anti-bot mechanisms
• Customizable Volume Control: Set limits on items per URL to manage data collection scope and optimize scraping costs
• Error Resilience: Automatic retry mechanisms and failure handling ensure maximum data collection success

Who Benefits from This Scraper?

The Willhaben.at Jobs Scraper serves diverse professional needs:

• Recruitment Agencies: Monitor competitor job postings, identify hiring trends, and discover potential client companies
• HR Professionals: Benchmark salaries, analyze employment terms, and understand market compensation standards
• Business Analysts: Track industry hiring patterns, identify growth sectors, and conduct market research
• Job Aggregators: Build comprehensive job databases by collecting listings from Austria's leading employment platform
• Academic Researchers: Study employment trends, labor market dynamics, and economic indicators

Input Configuration Explained

Example url 1: https://www.willhaben.at/jobs/suche?keyword=Tankstelle

Example url 2: https://www.willhaben.at/jobs/suche/vollzeit

Example url 3: https://www.willhaben.at/jobs/suche?keyword=Teilzeit&page=2

Example Screenshot of jobs list by query page:

Input Format Specification

The scraper accepts JSON configuration with precise parameters to customize data extraction according to specific requirements. The input structure includes essential settings for proxy configuration, retry mechanisms, and URL specifications.

Example Input Configuration:

{
  "max_retries_per_url": 2, // Maximum waiting time when accessing the links you provided.
  "proxy": { // Add a proxy to ensure that during the data collection process, you are not detected as a bot.
    "useApifyProxy": true,
    "apifyProxyGroups": [
      "RESIDENTIAL" 
    ],
    "apifyProxyCountry": "SG" // You should choose an Country that coincides with the Country you want to collect data from
  },
  "max_items_per_url": 20,
  "ignore_url_failures": true,
  "urls": [ // Links to jobs list by query pages.
    "https://www.willhaben.at/jobs/suche?keyword=Tankstelle",
    "https://www.willhaben.at/jobs/suche/vollzei",
    "https://www.willhaben.at/jobs/suche?keyword=Teilzeit&page=2"
  ]
}

Parameter Explanations:

Parameter Explanations

max_retries_per_url (integer): Defines how many times the scraper will attempt to access a URL if the initial request fails. A value of 2 provides a good balance between persistence and efficiency—if a page is temporarily unavailable, the scraper will try twice more before moving on.

proxy (object): Configures proxy settings for anonymous and reliable scraping:

• useApifyProxy: When set to true, routes requests through Apify's proxy network
• apifyProxyGroups: Specifies proxy type; RESIDENTIAL proxies use real residential IP addresses, making requests appear as regular user traffic and reducing detection risk
• apifyProxyCountry: Sets the geographic location of proxy IPs. Using "AT" (Austria) is recommended for willhaben.at to match the target audience's location and improve success rates

max_items_per_url (integer): Limits the number of job listings extracted from each URL. This helps control scraping volume and costs. For example, setting this to 20 means you'll get up to 20 job listings from each search URL provided.

ignore_url_failures (boolean): When true, the scraper continues processing remaining URLs even if one fails. This ensures partial data collection rather than complete failure.

urls (array): Contains the list of willhaben.at job search URLs to scrape.

Input Requirements and Best Practices

• URL Format: URLs must be valid willhaben.at job search pages. The scraper works with search results pages, not individual job detail pages
• Proxy Country Selection: Choose Austria ("AT") for the apifyProxyCountry to align with the target website's primary audience
• Volume Management: Start with smaller max_items_per_url values (10-20) for testing, then increase for production runs
• Multiple Queries: Include diverse search URLs to capture different job categories, locations, or employment types in one scraping session

Comprehensive Output Data Structure

You get the output from the willhaben.at Jobs Search Scraper stored in a tab. The following is an example of the Information Fields collected after running the Actor.

[ // List of jobs information
  {
  "id": 12792661,
  "title": "LKW-Fahrer mit C und E Führerschein (m/w/d)",
  "slug_title": "lkw-fahrer-mit-c-und-e-fuehrerschein-m-w-d",
  "creation_date": "2023-03-07T09:53:13.197559",
  "url": "jobs/job/lkw-fahrer-mit-c-und-e-fuehrerschein-m-w-d/12792661",
  "first_publish_date": "2023-03-07T09:53:12.128",
  "last_reorder_date": "2025-10-28T01:50:00.005",
  "is_expired": false,
  "overpay": false,
  "top_job": true,
  "position": "Mitarbeiter:in",
  "job_locations": [
    {
      "name": "Amstetten"
    },
    {
      "name": "Amstetten"
    },
    {
      "name": "Ennsdorf"
    }
  ],
  "description": "LKW-Fahrer mit C und E Führerschein (m/w/d) \nSaexinger Ges.m.b.H. \nEnnsdorf, Amstetten, Amstetten \nFür unseren Transportbereich suchen wir zum sofortigen Eintritt einen LKW-Fahrer (m/w/d) zur Verstärkung unseres Teams.\nIhre Aufgaben\n\n* regionale Auslieferung Österreich auf Tagestourenbasis bzw. 2-Tagestourenbasis \n* 5 Tage-Woche (Montag bis Freitag) \n* Auslieferung von Gefahrgütern bzw. Thermo-Güter \n* Selbstständige Be- und Entladung des Fahrzeuges \n* Fachkundiger Umgang mit den Fahrzeug und Thermoaggregaten \n* Einhaltung sämtlicher gesetzlicher und sicherheitstechnischer Vorschriften \n* Freundliches und kundenorientiertes Auftreten \n* Fahrer ist Repräsentant des Unternehmens nach AußenIhr Profil\n\n* B, C und E Führerschein \n* Gültiger ADR-Schein von Vorteil \n* Abgeschlossene C95 Ausbildung \n* Mehrjährige einschlägige Berufserfahrung als Kraftfahrer \n* Gute DeutschkenntnisseFür diese Position bewegt sich das Bruttomonatsgehalt EUR 2.600 plus Tagesdiäten, Überstunden & Prämien.\nWenn Sie gerne unser Team verstärken wollen schreiben Sie eine aussagekräftige Bewerbung an karl.boentner@saexinger.at",
  "company": {
    "id": 2730127,
    "title": "Saexinger Ges.m.b.H.",
    "slug_title": "saexinger-ges-m-b-h",
    "logo_url": "https://www.willhaben.at/jobs/api/v1/images/public/10021660?resolution=480"
  },
  "last_modified_date": null,
  "salary": 15.03,
  "salary_time_frame": null,
  "employment_time": "ab sofort",
  "employment_modes": [
    "Vollzeit"
  ],
  "brand_new": false,
  "internal_application": true,
  "from_url": "https://www.willhaben.at/jobs/suche/vollzeit"
}, // ... Many other jobs details
]

The scraper extracts the following fields for each job listing:

ID (string): A unique identifier assigned by willhaben.at to each job posting. This serves as a primary key for database storage and enables tracking of specific listings over time for monitoring purposes such as identifying when jobs are reposted or removed.

Title (string): The job position name as advertised by the employer. This is the main heading job seekers see and typically includes the role name and sometimes seniority level. Use this field for job categorization, keyword analysis, and matching candidates to positions.

Slug Title (string): A URL-friendly version of the job title, formatted with hyphens instead of spaces and special characters removed. This is used in the job's web address and can serve as a human-readable unique identifier in your systems.

Creation Date (datetime): The timestamp when the job listing was first created in willhaben's system. This helps you identify the freshest opportunities and calculate how long positions remain open—valuable for understanding hiring urgency and market competition.

URL (string): The direct link to the job's detail page on willhaben.at. Essential for linking users to full job descriptions, application forms, and enabling candidates to apply directly through the platform.

First Publish Date (datetime): When the job was first made visible to the public. This may differ from creation date if employers prepared listings in advance. Use this to track actual market exposure time.

Last Reorder Date (datetime): Indicates when the employer paid to promote or "bump" the listing to appear higher in search results. Recent reorder dates suggest active hiring and employer investment in filling the position quickly.

Is Expired (boolean): Flags whether the job listing is still active (false) or has been closed/expired (true). Critical for filtering current opportunities and cleaning outdated data from your database.

Overpay (boolean): Indicates if the position offers above-market compensation. This premium feature allows employers to highlight competitive salaries, helping you identify high-value opportunities or benchmark competitive compensation packages.

Top Job (boolean): Marks featured or promoted listings that employers paid to highlight. These positions typically receive more visibility and may indicate urgency or importance to the hiring company.

Position (string): The specific job role or title, sometimes more detailed than the Title field. May include department information, specialization areas, or seniority indicators that help with precise job classification.

Job Locations (array): Contains one or more geographic locations where the job is based. Can include cities, regions, or indicate remote work options. Essential for location-based filtering and understanding geographic hiring patterns.

Description (string): The complete job posting text including responsibilities, requirements, qualifications, benefits, and company information. This rich-text field is valuable for natural language processing, keyword extraction, and skills analysis.

Company (string): The hiring organization's name. Use this to track which companies are actively hiring, analyze employer hiring patterns, identify potential clients for B2B services, or monitor competitor recruitment activities.

Last Modified Date (datetime): The most recent timestamp when any aspect of the listing was updated. Helps identify jobs with recent changes to descriptions, requirements, or terms—potentially indicating hiring challenges or evolving role needs.

Salary (string): The compensation offered, when disclosed. May be formatted as a range, fixed amount, or text description. Critical for salary benchmarking, compensation analysis, and understanding market rates across industries and positions.

Salary Time Frame (string): Specifies the pay period for the stated salary (e.g., "per month", "per year", "per hour"). Essential for normalizing salary data across listings and accurately comparing compensation packages.

Employment Time (string): Indicates the duration or schedule of employment such as "full-time", "part-time", "contract", or specific hour requirements. Helps job seekers filter by availability and analysts understand employment type distribution.

Employment Modes (array): Details work arrangement options like "on-site", "remote", "hybrid", or specific flexibility terms. Increasingly important for modern work preference analysis and understanding employer flexibility offerings.

Brand New (boolean): Flags listings posted within the last 24-48 hours. Valuable for applications prioritizing fresh opportunities or monitoring real-time hiring activity.

Internal Application (boolean): Indicates if the position is an internal promotion opportunity versus external hiring. Useful for understanding company growth patterns and internal mobility rates.

Data Utilization Strategies

The extracted data supports numerous business applications:

• Salary Benchmarking: Aggregate salary data by position, industry, and location to establish competitive compensation ranges
• Hiring Trend Analysis: Track which companies are hiring, in what roles, and at what frequency to identify market expansion
• Skills Gap Analysis: Extract required skills from descriptions to understand in-demand competencies
• Geographic Insights: Map job concentration by region to identify economic hotspots or underserved markets
• Competitive Intelligence: Monitor competitor hiring patterns, organizational growth, and strategic priorities
• Job Board Enrichment: Populate job aggregator platforms with comprehensive Austrian employment data

How to Use the Willhaben.at Jobs Scraper

Step-by-Step Implementation

Step 1: Define Your Data Collection Scope Identify the job categories, keywords, locations, or companies you want to target. Browse willhaben.at/jobs manually to construct appropriate search URLs that capture your target listings.

Step 2: Configure Input Parameters Create your JSON input configuration:

• Add your target URLs to the urls array
• Set max_items_per_url based on your data volume needs
• Configure proxy settings with apifyProxyCountry: "AT" for optimal results
• Set max_retries_per_url to 2-3 for reliability

Step 3: Execute the Scraper Run the scraper through your preferred platform (typically Apify). Monitor the execution log for progress updates and any error messages.

Step 4: Retrieve and Validate Data Download the extracted data in your preferred format (JSON, CSV, Excel). Validate data completeness by checking key fields like Title, Company, and URL.

Step 5: Process and Analyze Import data into your database, analytics platform, or business intelligence tools. Apply filters, aggregations, and visualizations to derive insights.

Tips for Optimal Results

• Schedule Regular Runs: Jobs data changes frequently; schedule daily or weekly scraping to maintain current information
• Use Specific Searches: Targeted search URLs yield more relevant results than broad queries
• Monitor for Changes: Track Last Modified Date to identify updated listings and salary adjustments
• Respect Rate Limits: While residential proxies reduce detection risk, implement reasonable delays between large scraping operations
• Data Deduplication: Use the ID field to prevent duplicate records when combining multiple scraping runs

Handling Common Issues

Empty Results: Verify your URLs are valid willhaben.at job search pages. Check if search queries return results when visited manually.

Incomplete Data: Some fields may be null if employers didn't provide that information. This is normal—not all listings include salary, exact locations, or all metadata.

Proxy Errors: If encountering frequent failures, ensure your proxy configuration is correct and you have sufficient proxy credits. Consider switching to Austrian proxies specifically.

Rate Limiting: If the scraper is blocked, reduce max_items_per_url, increase delays between requests, or ensure residential proxies are properly configured.

Benefits and Real-World Applications

Time and Cost Efficiency

Manual job data collection from willhaben.at is prohibitively time-consuming. Copying information from even 100 job listings could take 3-4 hours, and maintaining updated data requires repeating this process regularly. The scraper automates this task in minutes, freeing your team to focus on analysis and decision-making rather than data entry.

Practical Use Cases

Recruitment Optimization: Agencies use the scraper to monitor which companies are hiring in their specialization areas, enabling proactive client outreach and candidate matching.

Market Research: Business analysts track hiring volumes by industry and region to identify growth sectors and inform investment decisions or market entry strategies.

Compensation Planning: HR departments aggregate salary data to establish competitive pay scales, ensuring they attract talent without overpaying relative to market standards.

Competitive Analysis: Companies monitor competitor hiring patterns to understand rival expansion plans, technological focus areas, and talent acquisition strategies.

Job Aggregation: Employment platforms syndicate willhaben.at listings to provide comprehensive job coverage for Austrian job seekers, increasing their platform value.

Business Value

Access to structured, comprehensive job market data provides significant competitive advantages. Organizations can make data-driven hiring decisions, optimize recruitment budgets, identify emerging skill demands early, and respond quickly to market changes. For recruitment businesses, this intelligence directly translates to faster placements, better client service, and increased revenue.

Conclusion

The Willhaben.at Jobs Scraper transforms how organizations access and utilize Austrian employment market data. By automating the extraction of comprehensive job information from the country's leading employment platform, it enables businesses to make informed decisions based on current market intelligence rather than intuition or outdated information.

Whether you're optimizing recruitment strategies, conducting market research, benchmarking compensation, or building job aggregation services, this scraper provides the foundation for data-driven success in the Austrian employment market.

Ready to unlock the power of automated job data collection? Configure your scraper today and gain instant access to actionable employment market intelligence.

Related Actors

• willhaben.at Jobs Details Scraper: A specialized data extraction tool engineered to harvest detailed jobs information from willhaben's.

Your feedback

We are always working to improve Actors' performance. So, if you have any technical feedback about willhaben.at Jobs Search Scraper or simply found a bug, please create an issue on the Actor's Issues tab in Apify Console.