StepStone Jobs Scraper — DACH Job Listings | No Login

Extract job listings from StepStone.de — Germany's leading job board with over 60,000 active postings — into clean, structured JSON. No login required. No StepStone API key needed.

Pricing: Scraping 1,000 job listings costs approximately $2.90.

What it scrapes

For each job listing, the actor extracts:

Field	Description	Example
job_id	StepStone numeric listing ID	14081997
title	Job title	Agentic Software Engineer (m/w/d)
company	Employer name	Reply GmbH
location	City / region	Berlin, Hamburg
employment_type	Contract type	Permanent, Freelance, Internship
work_mode	Remote / hybrid / on-site	Home office possible, Hybrid
posted_date	Posting date (ISO-8601)	2026-06-04
job_url	Direct link to job page	https://www.stepstone.de/stellenangebote--...
description_snippet	Key bullet points from listing	Python, FastAPI, PostgreSQL | Microservices on AWS
scraped_at	Scrape timestamp (UTC)	2026-06-07T10:23:00Z
search_keyword	Keyword used to find this job	Software Engineer
search_location	Location filter applied	Berlin

How to use

1. Configure inputs

• Search keywords: One or more job titles or skill keywords. Each keyword runs separately. Examples: ["Software Engineer", "Data Analyst", "Product Manager"]
• Location: Optional city or region to filter results. Examples: Berlin, München, Frankfurt. Leave empty to search all of Germany.
• Max items: Total maximum records to collect across all keywords (default: 100).
• Max pages per keyword: How many result pages to fetch per keyword. Each page returns ~20 jobs. Default: 5 pages = ~100 jobs per keyword.
• Proxy configuration: Pre-configured with Apify RESIDENTIAL proxy (Germany) — required for StepStone's regional access. No changes needed.

2. Run the actor

Typical run times:

• 100 jobs: ~1–2 minutes
• 500 jobs: ~5–8 minutes
• 2,000 jobs: ~20–30 minutes

3. Download results

Results are available in JSON, CSV, XLSX, or XML format directly from the Apify dataset.

Example output

{
  "job_id": "14081997",
  "title": "Agentic Software Engineer (m/w/d)",
  "company": "Reply GmbH",
  "location": "Berlin",
  "employment_type": "Permanent",
  "work_mode": "Home office possible",
  "posted_date": "2026-06-05",
  "job_url": "https://www.stepstone.de/stellenangebote--Agentic-Software-Engineer--14081997-inline.html",
  "description_snippet": "Entwicklung KI-basierter Agentenlösungen | Zusammenarbeit mit cross-funktionalen Teams | Python, LangChain, OpenAI API",
  "scraped_at": "2026-06-07T10:23:00Z",
  "search_keyword": "Software Engineer",
  "search_location": "Berlin"
}

Example input

{
  "searchKeywords": ["Software Engineer", "Python Developer"],
  "location": "Berlin",
  "maxItems": 200,
  "maxPages": 10,
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": ["RESIDENTIAL"],
    "apifyProxyCountry": "DE"
  }
}

Coverage and scale

• ~60,000+ active listings across Germany, Austria, and Switzerland
• ~20 jobs per page, up to 25 pages per search (500 jobs per keyword with default settings)
• All job categories: IT/Tech, Engineering, Marketing, Finance, Sales, HR, Healthcare, and more
• All employment types: permanent, fixed-term, part-time, freelance, internship, apprenticeship

Use cases

• Talent intelligence: monitor competitor hiring velocity, headcount trends, tech stack signals
• Sales prospecting: identify companies actively growing a department (hiring = buying intent)
• Market research: analyze salary bands, required skills, geographic demand across the DACH market
• Job aggregation: build niche job boards or alerts for specific roles/cities
• Academic research: labor market studies, skills gap analysis, remote-work adoption trends

Technical approach

• Transport: Apify RESIDENTIAL proxy (Germany) for reliable regional access
• Parser: structural HTML parsing anchored on data-at attributes and tag hierarchy — resilient to CSS class changes
• Deduplication: cross-keyword deduplication by job ID — no duplicate records even when keywords overlap
• Pagination: automatic pagination up to maxPages; stops early if no next page detected

Legal disclaimer

This actor scrapes publicly visible job listings from StepStone.de, which are freely accessible to all internet users without login. No user accounts, paywalled content, or personally identifiable information (PII) is accessed. Use in compliance with StepStone's Terms of Service and applicable data protection regulations (GDPR). This actor is intended for market intelligence and research purposes.

FAQ

Does this require a StepStone account? No. All scraped data is from public listings visible without login. Salary details are hidden behind login and are not scraped.

Why does it use a residential proxy? StepStone.de requires EU residential proxies — datacenter IP ranges are not reliable. EU residential proxies (included via Apify proxy) pass this transparently. The proxy cost is included in the per-listing price.

Can I scrape a specific city outside Germany? Yes — StepStone serves Austria (Wien, Graz) and Switzerland (Zürich, Basel). Use city name in the location field.

What happens if a keyword returns no results? The actor logs a warning and moves to the next keyword. Zero results are not charged.

More scrapers from our toolkit

Building a data pipeline? These actors pair well with this one — each runs on your own Apify account with the same pay-per-result pricing, no subscription:

• Workable Job Scraper
• Xing Jobs Scraper
• Ashby Job Scraper
• Dice Jobs Scraper
• Glassdoor Scraper
• Greenhouse Job Scraper

Chain any of them together from the Integrations tab (the Run succeeded trigger) to build a multi-step workflow — one actor's output feeds the next.

Usage statistics

This Actor creates a small, content-free summary at the end of each run. It is used only to monitor reliability and improve this Actor. A copy is saved as USAGE_STATS in your own Apify key-value store, so you can see the exact record created for your run.

Set disableUsageStats to true in the input to opt out. Nothing is sent then; your USAGE_STATS record only says that statistics were disabled.

Only these fields are recorded:

• schema version, Actor name and build number;
• UTC start and finish hour (not a precise timestamp);
• run duration, number of results and time to the first result, each as a coarse range;
• whether the result was empty, the end status, and an error type from a fixed list;
• memory setting and counts of charged events;
• names of the input fields you set, never their values;
• the selected option for input fields that offer a fixed list of choices (for example a sort order).

We do not collect input text, search terms, URLs, domains, usernames, email addresses, names, proxy credentials, tokens, scraped records, output items, raw error messages, stack traces, or hashes of any of those values. Records are kept for no longer than 13 months, used only as aggregated operational statistics, and never sold or shared.

Additional fields (Phase 2)

This Actor also records your Apify user ID, whether Apify marks the account as paying, the size range of list inputs, the selected country when the input offers a fixed list of countries, and one category from a fixed Actor taxonomy. We use these fields only for aggregate reliability, repeat-use and cross-Actor analysis; reports suppress any cell with fewer than five distinct users.

The same disableUsageStats: true input flag turns these fields off too. The user ID is removed after 13 months; we do not export, sell, share, or attempt to re-identify this data.

Run-outcome signals (v2)

To learn whether a run did what it was asked to do, the record also holds a few more coarse ranges and yes/no flags. None of them contains content:

• the result limit you asked for (a range, when the input has one) and what share of it was delivered;
• results delivered per input item you listed (a range);
• output quality as ranges: how fully the result fields were filled, the share of rows that look like errors, the share of duplicate rows, and how many different fields appeared. These are counted in memory while results are saved; no result content is kept;
• how the run was started (console, API, schedule, webhook, another Actor);
• how it ended: stopped by you, timed out, reached the requested limit, stopped by the charge limit, and how many times the platform moved the run;
• if this Actor reports it: how many items to process worked or failed (ranges) and one failure reason from a fixed list;
• a short code made from the names of the input fields you set, never their values.

Repeat-run fingerprint (v2)

When your Apify user ID is recorded (see above), the record also holds an 8-character one-way code made from your input (proxy settings left out) and this Actor's name. It only lets us see that the same account ran the same input again soon after an unsatisfying run; we never see the input itself. It is stored only in the database, never published, and reports use it in aggregate with the same five-user minimum. It is the one exception to the statement above that no hashes are collected, and disableUsageStats: true turns it off.