# StepStone Jobs Scraper (`datascrapers/stepstone-jobs-scraper`) Actor

Scrapes job listings from StepStone (stepstone.de and other StepStone sites). Supports direct search URLs or keyword/location/filter input with pagination.

- **URL**: https://apify.com/datascrapers/stepstone-jobs-scraper.md
- **Developed by:** [Farhan Ali](https://apify.com/datascrapers) (community)
- **Categories:** Jobs, Lead generation, Integrations
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.70 / 1,000 jobs

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#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

**StepStone Jobs Scraper** creates a structured dataset of job listing records collected from StepStone (stepstone.de and other StepStone country sites). Each dataset item can include the job title, company, location, posting date, salary range, remote-work label, labels, text snippet, and URLs. Query the source using direct search URLs or keyword/location filters, control the result limit with `maxItems`, and retrieve records through the Apify Dataset API or export them as JSON, CSV, Excel, or XML.

### Dataset at a glance

| Property | Value |
|---|---|
| Source | stepstone.de, stepstone.at, stepstone.be, stepstone.nl |
| Record unit | One job listing |
| Input methods | Direct search URLs, or keyword and location filters |
| Main identifiers | `id`, `harmonisedId`, `url` |
| Delivery | Apify Dataset and API |
| Export formats | JSON, CSV, Excel, XML |
| Update model | Fresh records per Actor run |
| Pricing | Pay per event — $1 per 1,000 listings |

### Coverage and available records

- **Supported inputs** — Direct StepStone search URLs (`https://www.stepstone.de/jobs/python/in-berlin?radius=30`) or a combination of `searchQueries` and `searchLocations`.
- **Country sites** — `baseUrl` selects stepstone.de, stepstone.at, stepstone.be, or stepstone.nl when building URLs from keywords.
- **Filters** — `radius` controls the search distance around each location; `searchFilters` appends arbitrary StepStone query parameters (e.g. sort, employmentType) to built URLs.
- **Pagination** — Results are paginated through StepStone's result list API until `maxItems` is reached.
- **Salary data** — `salaryMin`, `salaryMax`, `salaryCurrency`, and related fields are captured when the listing publishes a range.
- **Not currently collected** — Full job descriptions from the detail page and company profile data.

### Data dictionary

| Field | Type | Nullable | Description | Example |
|---|---:|---|---|---|
| `id` | number | Yes | Numeric StepStone job ID | `12345678` |
| `harmonisedId` | string | Yes | Normalized identifier across StepStone sites | `stepstone-12345678` |
| `title` | string | No | Job title | `Python Entwickler (m/w/d)` |
| `url` | string | No | Job listing URL | `https://www.stepstone.de/stellenanzeige/...` |
| `companyName` | string | Yes | Company name | `Tech Startup GmbH` |
| `companyUrl` | string | Yes | Company website or profile URL | `https://www.techstartup.de` |
| `companyLogoUrl` | string | Yes | Company logo URL | `https://www.stepstone.de/logo/98765` |
| `location` | string | Yes | Job location | `Berlin, Deutschland` |
| `postCode` | string | Yes | Postal code | `10115` |
| `datePosted` | string | Yes | Posting timestamp (ISO 8601) | `2026-07-22T08:15:00Z` |
| `textSnippet` | string | Yes | Short listing description | `Wir suchen einen erfahrenen...` |
| `labels` | array | Yes | Employment labels (e.g. full-time) | `["Vollzeit", "Unbefristet"]` |
| `skills` | array | Yes | Listed skills | `["Python", "Django", "Docker"]` |
| `salaryMin` / `salaryMax` | number | Yes | Salary range | `60000` / `85000` |
| `salaryCurrency` | string | Yes | Salary currency code | `EUR` |
| `salaryPeriod` | string | Yes | Salary period | `YEAR` |
| `workFromHome` | string | Yes | Remote-work flag | `2` |
| `workFromHomeLabel` | string | Yes | Human-readable remote label | `Remote possible` |
| `isTopJob` | boolean | Yes | Whether the listing is a top job | `true` |
| `searchUrl` | string | Yes | Search URL that produced the record | `https://www.stepstone.de/jobs/python/in-berlin?radius=30` |
| `page` | number | Yes | Result page number | `1` |

### Example dataset record

```json
{
  "id": 12345678,
  "harmonisedId": "stepstone-12345678",
  "title": "Python Entwickler (m/w/d)",
  "url": "https://www.stepstone.de/stellenanzeige/python-entwickler-12345678",
  "companyName": "Tech Startup GmbH",
  "companyUrl": "https://www.techstartup.de",
  "location": "Berlin, Deutschland",
  "postCode": "10115",
  "datePosted": "2026-07-22T08:15:00Z",
  "textSnippet": "Wir suchen einen erfahrenen Python Entwickler für unser dynamisches Team in Berlin.",
  "labels": ["Vollzeit", "Unbefristet"],
  "skills": ["Python", "Django", "PostgreSQL", "Docker"],
  "salaryMin": 60000,
  "salaryMax": 85000,
  "salaryCurrency": "EUR",
  "salaryPeriod": "YEAR",
  "workFromHomeLabel": "Remote possible",
  "isTopJob": true,
  "searchUrl": "https://www.stepstone.de/jobs/python/in-berlin?radius=30",
  "page": 1
}
```

This record was produced from the search URL `https://www.stepstone.de/jobs/python/in-berlin?radius=30`.

### Query and input reference

| Input | Type | Required | Default | Accepted values | Description |
|---|---:|---|---|---|---|
| `startUrls` | array | No | — | StepStone search URLs | Direct URLs to scrape |
| `searchQueries` | array | No | — | Job keywords (`python`, `data engineer`) | Combined with OR |
| `searchLocations` | array | No | — | City or region names | Omit to search nationwide |
| `radius` | integer | No | `30` | `0`–`200` km | Distance around each location |
| `searchFilters` | object | No | `{}` | Additional query parameters | Ignored when using `startUrls` |
| `baseUrl` | string | No | `https://www.stepstone.de` | `stepstone.de`, `stepstone.at`, `stepstone.be`, `stepstone.nl` | Country site for built URLs |
| `maxItems` | integer | No | `0` | `0` = unlimited | Max job records to scrape |
| `proxyConfiguration` | object | No | Residential | Apify proxy config | Residential proxy recommended |

Minimal request:

```json
{ "searchQueries": ["python"], "searchLocations": ["Berlin"] }
```

Advanced request:

```json
{
  "searchQueries": ["python", "data engineer"],
  "searchLocations": ["Berlin"],
  "radius": 30,
  "baseUrl": "https://www.stepstone.de",
  "maxItems": 500,
  "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": ["RESIDENTIAL"], "apifyProxyCountry": "DE" }
}
```

### Retrieve the data through the API

1. Start the Actor with a JSON input via the Apify API or the Actor's API tab.
2. Wait for the run to finish.
3. Retrieve items from the run's default dataset.
4. Paginate or export the dataset in JSON, CSV, Excel, or XML.

```python
from apify_client import ApifyClient

client = ApifyClient("YOUR_API_TOKEN")
run = client.actor("datascrapers/stepstone-jobs-scraper").call(
    run_input={"searchQueries": ["python"], "searchLocations": ["Berlin"], "maxItems": 300}
)
items = client.dataset(run["defaultDatasetId"]).list_items().items
```

### Data quality and record handling

- **Completeness** — Title, company, location, and URL are present on most listings; salary and skill fields are conditional on what the listing publishes.
- **Deduplication** — Use `harmonisedId` (preferred) or `id` as the stable external key across StepStone sites.
- **Retries** — StepStone blocks datacenter IPs; residential proxies are recommended to reduce failures.
- **Normalization** — `salaryMin`/`salaryMax` are numbers with a separate `salaryCurrency`; dates use ISO 8601 timestamps.
- **Raw vs derived** — All fields are taken directly from StepStone's result list API; no AI-generated or computed values are added.

### Export and pipeline examples

| Destination | Recommended method | Typical use |
|---|---|---|
| PostgreSQL/Supabase | Dataset API or webhook consumer | Job board keyed by `harmonisedId` |
| Google Sheets | Apify integration | Market-rate salary analysis |
| S3/cloud storage | Scheduled export or integration | Daily job-market ingestion |

### Pricing and cost examples

Billing is pay-per-event, tiered across Apify plans; the rate below is the free-plan rate.

| Event | Charged when | Free-plan rate |
|---|---|---|
| `dataset-item` (job) | A job listing is pushed to the dataset | $1 per 1,000 listings |

A fixed one-time Actor Start charge of $0.00005 also applies to each run.

| Listings | Estimated base cost |
|---:|---:|
| 1,000 | $1 |
| 10,000 | $10 |

Estimates depend on the pricing model and the options enabled.

### Limitations and responsible data use

- Only publicly accessible StepStone job listings are collected.
- Full job descriptions and company profiles are not collected; listings carry a short `textSnippet`.
- Salary and skill fields are conditional and may be empty when the listing omits them.
- No historical snapshots are stored unless you persist them yourself across scheduled runs.
- You are responsible for complying with StepStone's terms and applicable privacy and data laws.

### Dataset questions

#### What does one dataset item represent?

One job listing from the StepStone result list.

#### Which field should I use as a unique identifier?

`harmonisedId` is normalized across StepStone country sites; `id` is the raw numeric ID.

#### Are fields nullable or conditional?

Yes. Salary, skills, and remote-work fields are conditional on what each listing publishes.

#### Can I retrieve the records as CSV or JSON?

Yes. The default dataset can be exported as JSON, CSV, Excel, or XML from the Apify Console or via the Dataset API.

#### How do I paginate large datasets?

The Actor paginates automatically up to `maxItems`. For very large exports, page through the dataset with the Dataset API `offset` and `limit` parameters.

#### What counts as a billable result?

Each job listing written to the dataset is one `dataset-item` event.

### Related datasets from Data Scrapers

- [LinkedIn Company Scraper](https://apify.com/datascrapers/linkedin-company-scraper) — company details for employer research alongside job listings.
- [LinkedIn Profile Scraper](https://apify.com/datascrapers/linkedin-profile-scraper) — professional profile data for recruiting pipelines.

### Data Scrapers support

Need an additional field, record type, or export workflow? Contact Data Scrapers at stardustspotlight@gmail.com. Include a sample source URL, required fields, expected record volume, and preferred delivery format.

# Actor input Schema

## `startUrls` (type: `array`):

Direct StepStone job search URLs to scrape. Use this OR searchQueries/searchLocations below — not both required.

## `searchQueries` (type: `array`):

Job keywords or titles to search for (e.g. python, data engineer). Combined with OR when multiple values are provided.

## `searchLocations` (type: `array`):

City or region names to filter results (e.g. Berlin, München). Optional — omit to search nationwide.

## `radius` (type: `integer`):

Radius around each location in kilometers. Only used when building URLs from searchQueries/searchLocations.

## `searchFilters` (type: `object`):

Additional StepStone query parameters appended to built search URLs (e.g. sort, employmentType, workFromHome, whatType). Ignored when using startUrls.

## `baseUrl` (type: `string`):

StepStone site origin used when building search URLs from keywords.

## `maxItems` (type: `integer`):

Maximum number of job records to scrape (0 = unlimited).

## `proxyConfiguration` (type: `object`):

Apify residential proxy is strongly recommended — StepStone blocks datacenter IPs.

## Actor input object example

```json
{
  "startUrls": [
    {
      "url": "https://www.stepstone.de/jobs/python/in-berlin?radius=30"
    }
  ],
  "searchQueries": [
    "python"
  ],
  "searchLocations": [
    "Berlin"
  ],
  "radius": 30,
  "searchFilters": {},
  "baseUrl": "https://www.stepstone.de",
  "maxItems": 25,
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": [
      "RESIDENTIAL"
    ]
  }
}
```

# Actor output Schema

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

Dataset containing scraped StepStone job listings

## `runStats` (type: `string`):

Aggregate scrape statistics for this run

# 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 = {
    "startUrls": [
        {
            "url": "https://www.stepstone.de/jobs/python/in-berlin?radius=30"
        }
    ],
    "searchQueries": [
        "python"
    ],
    "searchLocations": [
        "Berlin"
    ],
    "searchFilters": {},
    "maxItems": 25,
    "proxyConfiguration": {
        "useApifyProxy": true,
        "apifyProxyGroups": [
            "RESIDENTIAL"
        ]
    }
};

// Run the Actor and wait for it to finish
const run = await client.actor("datascrapers/stepstone-jobs-scraper").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 = {
    "startUrls": [{ "url": "https://www.stepstone.de/jobs/python/in-berlin?radius=30" }],
    "searchQueries": ["python"],
    "searchLocations": ["Berlin"],
    "searchFilters": {},
    "maxItems": 25,
    "proxyConfiguration": {
        "useApifyProxy": True,
        "apifyProxyGroups": ["RESIDENTIAL"],
    },
}

# Run the Actor and wait for it to finish
run = client.actor("datascrapers/stepstone-jobs-scraper").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 '{
  "startUrls": [
    {
      "url": "https://www.stepstone.de/jobs/python/in-berlin?radius=30"
    }
  ],
  "searchQueries": [
    "python"
  ],
  "searchLocations": [
    "Berlin"
  ],
  "searchFilters": {},
  "maxItems": 25,
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": [
      "RESIDENTIAL"
    ]
  }
}' |
apify call datascrapers/stepstone-jobs-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,datascrapers/stepstone-jobs-scraper"
        }
    }
}

```

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/IC4xxn6ll4BixhDpf/builds/mIqQjcgvA0zGQZhND/openapi.json