Stepstone Job Scraper 🔥

What does StepStone.de Job Scraper do?

StepStone.de Job Scraper collects public job listings from StepStone Germany and returns one clean record per job. Run it with a search keyword, a category, or a StepStone search URL. It saves the job title, company, location, posting date, job type, category, salary information, the original job URL, and the full job description as both HTML and plain text.

Use it for recruiting research, job market monitoring, salary analysis, lead lists for employers, and datasets that feed dashboards or AI assistants. Results arrive in the Apify dataset, ready for JSON, CSV, Excel, XML, or API access.

Why use StepStone.de Job Scraper?

• One record per job - Each item combines the search card and the job page, so you do not have to join two datasets.
• Full descriptions - Job pages are fetched for the complete description instead of a short search snippet.
• Salary awareness - When StepStone shows a salary range or an estimated range, the value is saved and marked as estimated when appropriate.
• Simple inputs - Use a keyword, a category path, or a full StepStone search URL.
• Repeatable runs - Schedule the Actor to track new postings, changed salaries, or hiring activity over time.
• Failure recovery - Temporary network and access failures are retried with a new request context. Expired jobs are skipped without stopping the run.

What data can you extract from StepStone.de?

Field	Description
title	Job title as shown on StepStone
company	Hiring company name
location	City, region, and country when published
date_posted	ISO date and time for when the job went online
job_type	Employment type such as FULL_TIME, or the work and contract type shown on the job page
job_category	Industry or occupational category
salary	Salary range, exact value, or estimated range. Predicted values include (estimated)
url	Direct StepStone job page URL without tracking parameters
description_html	Sanitized job description HTML with safe links
description_text	Plain text version of the job description

Some jobs do not publish a salary, a company name, or a precise location. Those fields stay empty instead of being filled with guessed values.

How to use StepStone.de Job Scraper

1. Open the Actor in Apify Console.
2. Choose one search method: enter a keyword, enter a category, or paste a StepStone search URL.
3. Set the maximum number of jobs and the maximum number of result pages.
4. Keep detail collection enabled if you need full descriptions and job page metadata.
5. Start the run and open the dataset when it finishes.
6. Download the dataset or connect it to Google Sheets, a webhook, or your own API.

The default input collects 20 jobs from the StepStone administration category. You can replace it with any public StepStone search.

Input Parameters

Parameter	Type	Required	Default	Description
startUrl	String	No	https://www.stepstone.de/jobs/verwaltung	StepStone search, category, or employer page to start from
keyword	String	No	-	Search keyword such as softwareentwickler. Takes precedence over category and startUrl
category	String	No	-	Category path segment such as it or engineering. Used when no keyword is supplied and takes precedence over startUrl
collectDetails	Boolean	No	true	Read each job page for the full description and extra metadata. When disabled, the Actor saves only job URLs
maxItems	Integer	No	20	Maximum number of jobs to save. Use 0 to keep collecting until the page limit or the last results page
maxPages	Integer	No	5	Maximum number of search result pages to read. Use 0 to apply the 200-page safety limit
proxyConfiguration	Object	No	German residential Apify Proxy	Proxy settings used for the run. StepStone limits access from many networks, so a German residential proxy is recommended

Only one search method is needed. If you provide more than one, the Actor uses keyword first, then category, then startUrl.

Output Data

Field	Type	Description
title	String or null	Job title
company	String or null	Hiring company
location	String or null	Job location
date_posted	String or null	ISO posting date
job_type	String or null	Employment, work, or contract type
job_category	String or null	Industry or occupational category
salary	String or null	Salary text, with (estimated) when the value is predicted
url	String	Direct job page URL
description_html	String or null	Sanitized description HTML
description_text	String or null	Description as plain text

When collectDetails is disabled, each record contains only the url field.

Usage Examples

Collect jobs by keyword

Search for software roles and save the first 50 jobs with full descriptions.

{
  "keyword": "softwareentwickler",
  "maxItems": 50,
  "maxPages": 3,
  "collectDetails": true
}

Collect jobs from a category

Collect administration jobs from the category path when you do not have a keyword.

{
  "category": "verwaltung",
  "maxItems": 30,
  "maxPages": 2,
  "collectDetails": true
}

Use a StepStone search URL

Start from any public StepStone search page, including a location-filtered search.

{
  "startUrl": "https://www.stepstone.de/jobs/softwareentwickler/in-berlin",
  "maxItems": 25,
  "maxPages": 1,
  "collectDetails": true
}

Collect job URLs only

Skip job page requests when you only need links for another tool or a later run.

{
  "keyword": "pflege",
  "maxItems": 100,
  "maxPages": 4,
  "collectDetails": false
}

Use your own proxy

Provide a proxy when you do not want to use the default Apify Proxy setting.

{
  "keyword": "data analyst",
  "maxItems": 20,
  "proxyConfiguration": {
    "useApifyProxy": false,
    "proxyUrls": [
      "http://username:password@proxy.example.com:8080"
    ]
  }
}

Sample Output

Example record from a real run. The description is shortened for readability.

{
  "title": "Softwareentwickler Microservice (w/m/d)",
  "company": "Bechtle AG",
  "location": "Neckarsulm, DE",
  "date_posted": "2026-10-21T09:39:37.02Z",
  "job_type": "FULL_TIME",
  "job_category": "IT, IT-Softwareentwicklung",
  "salary": "60000 - 81000 EUR per year (estimated)",
  "url": "https://www.stepstone.de/stellenangebote--Softwareentwickler-Microservice-w-m-d-Neckarsulm-Bechtle-AG--14672975-inline.html",
  "description_html": "<p>Bechtle ist einer der führenden IT-Dienstleister in Europa.</p><ul><li>Weiterentwicklung</li><li>Flexibilität</li></ul>",
  "description_text": "Bechtle ist einer der führenden IT-Dienstleister in Europa.\n- Weiterentwicklung\n- Flexibilität"
}

Tips for Best Results

• Keep maxItems small for the first run, then increase it after you confirm the search returns the jobs you expect.
• Use German job titles for broader coverage on StepStone Germany. For example, softwareentwickler usually returns more results than software engineer.
• Use a location path in startUrl when you need jobs from one city, such as /jobs/softwareentwickler/in-berlin.
• Keep collectDetails enabled when you need full descriptions. Disable it when you only need URLs.
• The default German residential proxy setting is recommended. Datacenter networks are often refused by StepStone.
• Job pages can expire between the search request and the detail request. The Actor skips expired jobs and continues the run.
• Salary values marked (estimated) are StepStone estimates, not employer-stated figures.

Integrations

• Google Sheets - Send job data to a spreadsheet for review or sharing.
• Webhooks - Start another workflow when a run finishes.
• Make or Zapier - Connect the dataset to no-code automations.
• Apify API - Read datasets from your own applications.
• CSV, Excel, JSON, XML - Download results in the format your tools already use.
• AI and RAG pipelines - Use description_text as clean input for search, classification, or matching.

Frequently Asked Questions

Can I export StepStone job data to CSV or Excel?

Yes. Every Apify dataset can be downloaded as CSV, Excel, JSON, XML, and other supported formats from the dataset view or through the API.

Can I run this Actor on a schedule?

Yes. Create an Apify schedule and choose how often the Actor should run, for example every day or every hour. Scheduled runs use the same input and save a new dataset each time.

How many jobs can one run collect?

The Actor reads 25 jobs per result page. The run stops at maxItems, maxPages, the last results page, an empty page, or a duplicate-only page. Very large runs depend on StepStone result limits and proxy usage.

Why are some fields empty?

StepStone does not publish every field for every job. A job may have no salary, no company name, or no precise location. The Actor leaves those fields empty instead of guessing.

Why does a job disappear between runs?

Employers can remove or expire a job at any time. The Actor skips an expired job page and keeps the rest of the run.

What does (estimated) mean in the salary field?

StepStone sometimes shows a predicted salary range instead of an employer-stated salary. The Actor keeps the range and adds (estimated) so you can separate predictions from stated pay.

Does the Actor collect personal data?

It collects job listing data that employers publish: job title, company, location, description, and salary information. It does not log in, bypass a paywall, or collect candidate data.

Can I use a custom proxy?

Yes. Set proxyConfiguration to your own proxy configuration. German residential proxies are recommended because StepStone limits access from many networks.

What happens if StepStone changes its page layout?

The Actor checks several places for job data on each page. If a run returns no jobs while the search page has results, open an issue with the run URL so the affected page shape can be inspected.

Is it legal to scrape StepStone?

Scraping public job data can be legal, but rules differ by jurisdiction and by website terms. You are responsible for using the Actor in compliance with applicable laws, StepStone terms, and privacy rules.

Support

For issues, feature requests, or custom Actor work, use the Issues tab on the Actor page or contact the developer through Apify. Include the run URL, the input used, and a short description of the expected result.

Legal Notice

This Actor collects publicly available job listings for legitimate use. Users are responsible for using the data responsibly and for complying with applicable laws, website terms, and privacy rules.