# Bundesagentur für Arbeit Scraper - Preiswert Low-cost 💲🔴💼 (`delectable_incubator/bundesagentur-fur-arbeit-scraper-preiswert-low-cost`) Actor

Scrape job listings from Germany using the Arbeitsagentur Jobs Scraper 🇩🇪💼

Extract offers by keyword and location, including job title, employer, occupation, publication date, location, and more.

Ideal for recruitment, job market analysis, and structured employment datasets 📊 Fast & scalable.

- **URL**: https://apify.com/delectable\_incubator/bundesagentur-fur-arbeit-scraper-preiswert-low-cost.md
- **Developed by:** [Prime Scrape](https://apify.com/delectable_incubator) (community)
- **Categories:** Jobs, Developer tools, Lead generation
- **Stats:** 4 total users, 3 monthly users, 100.0% runs succeeded, 1 bookmarks
- **User rating**: 5.00 out of 5 stars

## Pricing

from $0.00005 / actor start

This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

<p align="center"> <img src="https://i.ibb.co/jkNS73wX/readme.png" alt="Arbeitsagentur Job Scraper - Germany Official Job Data" width="100%"> </p>

***

### Bundesagentur für Arbeit Scraper | PrimeScrape 💼📊 Germany Official Job Data

Extract structured job listings directly from the official German employment portal (Arbeitsagentur / Bundesagentur für Arbeit) at scale.

This Apify Actor collects high-quality, verified job postings from Germany’s public job database, ideal for recruitment, analytics, and market intelligence.

Perfect for HR teams, recruiters, job boards, and data-driven hiring strategies 🚀📊

***

### Arbeitsagentur Job Scraper | PrimeScrape

Extrahieren Sie strukturierte Stellenanzeigen direkt aus dem offiziellen deutschen Jobportal Bundesagentur für Arbeit (arbeitsagentur.de).

Ideal für Recruiting, Arbeitsmarktanalyse, HR Intelligence und Jobdatenbanken in Deutschland 🇩🇪💼

***

### 🌍 What This Scraper Does

This scraper extracts job listings from: 👉 https://www.arbeitsagentur.de/jobsuche

It supports:

Bulk Keyword search (e.g. Softwareentwickler, Pflege, Ingenieur)

Location-based filtering

Radius search (km-based)

Sorting (Relevance, Latest, Entry date)

It automatically:

✔ Handles pagination

✔ Extracts structured job data

✔ Cleans employer & location metadata

✔ Returns ready-to-use datasets

***

### 🚀 Key Features

✔ Official German job portal data 🇩🇪

✔ High-quality verified listings

✔ Keyword + location + radius filtering

✔ Structured JSON / CSV / Excel output

✔ Fast & scalable scraping engine ⚡

✔ Perfect for HR & recruitment systems

***

### 📊 Data Extracted

📛 Job Title
🏢 Employer Name
📍 Location
🧑‍💼 Occupation Type
📝 Job Description (if available)
📅 Publication Date
📅 Start Date
💼 Employment Type
🌐 Job URL
📊 Job Reference ID
📍 Coordinates (lat/lon if available)
📏 Distance (if applicable)

***

### 📥 Input Example

```
{
  "keyword": "IT",
  "place": "Berlin",
  "sort_by": "Relevance",
  "rayon": "50 km",
  "maxitems": 100
}
```

| Field    | Type   | Description                                 |
| -------- | ------ | ------------------------------------------- |
| keyword  | string | Job search term (required)                  |
| place    | string | City / location                             |
| sort\_by  | string | Relevance / Latest publication / Entry date |
| rayon    | string | Search radius (Any, 10 km, 50 km, 100 km)   |
| maxitems | number | Maximum results to scrape                   |

***

### 📤 Output Example

```

{
  "title": "Softwareentwickler (m/w/d)",
  "reference": "14225-e8bdaf223de1868f-S",
  "occupation": "Softwareentwickler/in",
  "employer": "Cteam Consulting & Anlagenbau GmbH",
  "location": "Berlin",
  "region": "Berlin",
  "country": "Deutschland",
  "latitude": 52.4784,
  "longitude": 13.3541,
  "distance": "6",
  "publication_date": "2025-03-04",
  "start_date": "2025-03-16",
  "link": "https://www.jobvector.de/...",
  "link_to_profile": "https://www.arbeitsagentur.de/jobsuche/jobdetail/..."
}
```

***

### 🌐 Use Cases

💼 Recruitment & Talent Acquisition

📊 Labor Market Analysis (Germany)

🏢 Employer Intelligence & Benchmarking

📍 Regional Job Market Mapping

🤖 AI / Machine Learning Datasets

📬 Automated Job Alerts & Monitoring

***

### ⚙️ Why Use This Scraper?

📌 Access Germany’s official job database

📌 Build structured HR datasets at scale

📌 Analyze hiring trends & salary demand

📌 Automate recruitment pipelines

📌 Improve job board aggregation systems

***

### 🇩🇪 Supported Job Categories

✔ Software & IT Jobs

✔ Engineering

✔ Healthcare & Nursing

✔ Logistics & Transport

✔ Administration

✔ Skilled Trades

✔ Apprenticeships (Ausbildung)

✔ Public sector jobs

***

### ⚠️ Disclaimer

This tool is an independent solution and is not affiliated with, endorsed by, or sponsored by the Bundesagentur für Arbeit.

***

### 💸 Pricing

This scraper runs on a **pay per events subscription model**.

You only pay for **successful runs**.

💳 **Price:** $1.49 / 1000 results

***

### Related Actors

If you're interested in **other german** (trade fair / messe) data scraping solutions, explore more exhibitor & trade fair scrapers across Europe 🇩🇪🇪🇺

(Coming soon)

***

### 📬 Support

⭐ Leave a 5-star rating if you like this tool

***

### 🌍 PrimeScrape

Built for scalable web data extraction & automation

Contact for custom scraping solutions or enterprise requests via Apify or by email.

# Actor input Schema

## `queries` (type: `array`):

Enter keywords or search terms for job listings. / Gib Stichwörter oder Suchbegriffe für die Jobsuche ein.

## `place` (type: `string`):

Specify the city where you want to search for jobs. / Gib die Stadt an, in der du nach Jobs suchen möchtest.

## `maxitems` (type: `integer`):

Set the maximum number of job listings to scrape per query. / Lege die maximale Anzahl der zu scrapenden Jobangebote pro Suchbegriff fest.

## `sort_by` (type: `string`):

Choose how job listings should be sorted. / Wähle die Sortierung der Jobangebote.

## `rayon` (type: `string`):

Select the search radius for job listings. / Wähle den Umkreis für die Jobsuche.

## Actor input object example

```json
{
  "queries": [
    "IT",
    "Pflege"
  ],
  "place": "Berlin",
  "maxitems": 100,
  "sort_by": "Relevance",
  "rayon": "Any"
}
```

# Actor output Schema

## `results` (type: `string`):

No description

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "queries": [
        "IT",
        "Pflege"
    ],
    "place": "Berlin",
    "maxitems": 100,
    "sort_by": "Relevance",
    "rayon": "Any"
};

// Run the Actor and wait for it to finish
const run = await client.actor("delectable_incubator/bundesagentur-fur-arbeit-scraper-preiswert-low-cost").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "queries": [
        "IT",
        "Pflege",
    ],
    "place": "Berlin",
    "maxitems": 100,
    "sort_by": "Relevance",
    "rayon": "Any",
}

# Run the Actor and wait for it to finish
run = client.actor("delectable_incubator/bundesagentur-fur-arbeit-scraper-preiswert-low-cost").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "queries": [
    "IT",
    "Pflege"
  ],
  "place": "Berlin",
  "maxitems": 100,
  "sort_by": "Relevance",
  "rayon": "Any"
}' |
apify call delectable_incubator/bundesagentur-fur-arbeit-scraper-preiswert-low-cost --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,delectable_incubator/bundesagentur-fur-arbeit-scraper-preiswert-low-cost"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/ZzT4ojphP8ajewR5T/builds/c8xy75CQJm9BVwojd/openapi.json