# StepStone Jobs Scraper β High-Quality Job Data (From $0.9) (`ahmed_jasarevic/stepstone-job-scraper`) Actor
StepStone job scraper that extracts rich, structured job data via API. Collects titles, companies, locations, salaries, labels, work-from-home info, and full descriptions with fast pagination and clean normalized output ready for datasets, analytics, or job platforms.
- **URL**: https://apify.com/ahmed\_jasarevic/stepstone-job-scraper.md
- **Developed by:** [Ahmed Jasarevic](https://apify.com/ahmed_jasarevic) (community)
- **Categories:** Jobs, Developer tools, Automation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks
- **User rating**: No ratings yet
## Pricing
from $0.90 / 1,000 results
This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event
## What's an Apify Actor?
Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases.
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.
In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md):
```bash
npm install apify-client
```
In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md):
```bash
pip install apify-client
```
In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md):
````bash
# MacOS / Linux
curl -fsSL https://apify.com/install-cli.sh | bash
# Windows
irm https://apify.com/install-cli.ps1 | iex
```bash
In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md).
If your project is in a different language, use 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
## πΌπ StepStone Job Scraper (AI + IT + General Jobs API)
StepStone job scraper that extracts rich, structured job data via API. Collects titles, companies, locations, salaries, labels, work-from-home info, and full descriptions with fast pagination and clean normalized output ready for datasets, analytics, or job platforms.
It extracts structured job listings with full pagination support and normalized enterprise-grade output.
---
## π What this scraper does
This actor extracts **structured job market intelligence from StepStone**:
#### πΌ Job Data
* Job title
* Job ID (internal StepStone ID)
* Full job URL
* Section (main / promoted / sponsored)
* Labels (Quick Apply, Top Job, etc.)
---
#### π’ Company Data
* Company name
* Company ID
* Company profile URL
* Company logo
---
#### π Location & Work Setup
* City / region
* Remote / hybrid level (workFromHome)
* Job placement metadata
---
#### π° Salary Intelligence
* Min / max salary (if available)
* Currency
* Salary type (yearly/monthly)
* Salary availability flag
---
#### π Job Metadata
* Posting date
* Position ranking on page
* Absolute ranking across dataset
* Harmonised job ID (deduplication key)
---
#### π§ Enrichment Fields
* Skills (if available)
* Snippet / preview description
* Top labels (featured jobs, urgent, etc.)
* Sponsored / highlighted flags
---
#### π Pagination Engine
* Fully automatic multi-page crawling
* Stops when maxItems is reached
* Uses StepStone internal paging links
---
## βοΈ Input
### π Basic search example
```json
{
"startUrls": [
{
"url": "https://www.stepstone.de/jobs/ai?page=1&searchOrigin=Homepage_top-search"
}
],
"maxItems": 100,
"proxy": {
"useApifyProxy": true,
"apifyProxyGroups": ["RESIDENTIAL"]
}
}
````
***
### π§ Multi-category scraping
```json
{
"startUrls": [
{
"url": "https://www.stepstone.de/jobs/it-jobs"
},
{
"url": "https://www.stepstone.de/jobs/data-scientist"
}
],
"maxItems": 500
}
```
***
### β‘ High-scale mode
```json
{
"startUrls": [
{
"url": "https://www.stepstone.de/jobs/ai"
}
],
"maxItems": 10000,
"proxy": {
"useApifyProxy": true,
"apifyProxyGroups": ["RESIDENTIAL"]
}
}
```
***
## π Crawling Architecture
### π‘ API MODE (Core Engine)
This scraper uses StepStone internal endpoint:
```
POST /public-api/resultlist/unifiedResultlist
```
It handles:
- pagination links
- filtering
- job enrichment
- regional sorting
***
### π¦ Normalization Layer
Each job is transformed into:
- stable schema
- deduplicated structure
- enriched company mapping
- safe fallback values
***
## π€ Output
Each item represents **one job listing**.
***
### πΌ Example Output
```json
{
"id": 13953979,
"title": "Solution Architect - AI Applications (m/w/d)",
"labels": [],
"url": "https://www.stepstone.de/stellenangebote--Solution-Architect-AI-Applications-m-w-d-Bremen-Rheinmetall--13953979-inline.html?rltr=26_1_25_seorl_m_0_0_0_0_0_0",
"companyId": 1262,
"companyName": "Rheinmetall",
"companyUrl": "https://www.stepstone.de/cmp/de/rheinmetall-1262/jobs",
"companyLogoUrl": "https://www.stepstone.de/upload_DE/logo/B/logoRheinmetall-Group-1262DE-2101221907.gif",
"datePosted": "2026-04-27T04:16:49+02:00",
"location": "Bremen",
"isAnonymous": false,
"salary": "",
"postCode": null,
"partnership": {
"isPartnershipJob": false,
"showPartnershipLabel": false,
"isBackfilled": false,
"sourceSiteFriendlyName": "",
"isCrossPosted": false
},
"unifiedSalary": {
"min": null,
"max": null,
"currency": null,
"period": null,
"salaryAvailable": true,
"salaryType": null
},
"workFromHome": "2",
"metaData": {
"positionOnPage": 1,
"positionAbsolute": 26
},
"harmonisedId": "30619100-db32-4ad2-86b5-cfee63c36539",
"jobPostingSequence": null,
"periodPostedDate": null,
"publishFromDate": null,
"publishToDate": null,
"hasFuturePosting": false,
"fingerprintCount": null,
"section": "main",
"topLabels": [],
"skills": [],
"textSnippet": "Als Solution Designer (m/w/d) fΓΌr AI Applications verantworten Sie die technologische Produktplanung und die Umsetzung komplexer Softwareentwicklungsprojekte.",
"cvToJobScore": null,
"isHighlighted": false,
"isSponsored": false,
"travelTime": null,
"unifiedTravelTime": null,
"isTopJob": false,
"isTrafficFromPartner": false,
"sourceUrl": "https://www.stepstone.de/jobs/ai?page=2&searchOrigin=Homepage_top-search"
}
```
***
## π Features
- β‘ High-speed API scraping (no DOM scraping needed)
- π Full pagination support
- π§ Smart normalization layer
- π’ Company enrichment
- π Work-from-home detection
- π° Salary structure parsing
- 𧩠Clean dataset output (ETL ready)
***
## π‘ Use Cases
- AI job market tracking
- Recruitment intelligence systems
- Salary analytics
- Talent sourcing tools
- Job board aggregation
- HR data pipelines
***
## β οΈ Notes
- Residential proxy recommended for stability
- Works best with AI / IT / Germany job queries
- Designed for scalable production scraping
# Actor input Schema
## `startUrls` (type: `array`):
Stepstone.de search URLs (e.g., https://www.stepstone.de/jobs/ai?page=2\&searchOrigin=Homepage\_top-search)
## `maxItems` (type: `integer`):
Maximum number of listings to collect. Set to 0 for unlimited.
## `proxy` (type: `object`):
Residential proxies are mandatory for Funda to avoid blocks and interstitials.
## Actor input object example
```json
{
"startUrls": [
{
"url": "https://www.stepstone.de/jobs/ai?page=2&searchOrigin=Homepage_top-search"
}
],
"maxItems": 10,
"proxy": {
"useApifyProxy": true,
"apifyProxyGroups": [
"RESIDENTIAL"
]
}
}
```
# Actor output Schema
## `datasetItems` (type: `string`):
Scraped job listings from Stepstone unified API
## `datasetUrl` (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 '' with your token
const client = new ApifyClient({
token: '',
});
// Prepare Actor input
const input = {
"startUrls": [
{
"url": "https://www.stepstone.de/jobs/ai?page=2&searchOrigin=Homepage_top-search"
}
]
};
// Run the Actor and wait for it to finish
const run = await client.actor("ahmed_jasarevic/stepstone-job-scraper").call(input);
// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`πΎ 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);
});
// π Want to learn more π? Go to β 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 '' with your token.
client = ApifyClient("")
# Prepare the Actor input
run_input = { "startUrls": [{ "url": "https://www.stepstone.de/jobs/ai?page=2&searchOrigin=Homepage_top-search" }] }
# Run the Actor and wait for it to finish
run = client.actor("ahmed_jasarevic/stepstone-job-scraper").call(run_input=run_input)
# Fetch and print Actor results from the run's dataset (if there are any)
print("πΎ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
print(item)
# π Want to learn more π? Go to β https://docs.apify.com/api/client/python/docs/quick-start
```
## CLI example
```bash
echo '{
"startUrls": [
{
"url": "https://www.stepstone.de/jobs/ai?page=2&searchOrigin=Homepage_top-search"
}
]
}' |
apify call ahmed_jasarevic/stepstone-job-scraper --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=ahmed_jasarevic/stepstone-job-scraper",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "StepStone Jobs Scraper β High-Quality Job Data (From $0.9)",
"description": "StepStone job scraper that extracts rich, structured job data via API. Collects titles, companies, locations, salaries, labels, work-from-home info, and full descriptions with fast pagination and clean normalized output ready for datasets, analytics, or job platforms.",
"version": "1.0",
"x-build-id": "7VFLQ3xNjIMXjIkAo"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/ahmed_jasarevic~stepstone-job-scraper/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-ahmed_jasarevic-stepstone-job-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/ahmed_jasarevic~stepstone-job-scraper/runs": {
"post": {
"operationId": "runs-sync-ahmed_jasarevic-stepstone-job-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/ahmed_jasarevic~stepstone-job-scraper/run-sync": {
"post": {
"operationId": "run-sync-ahmed_jasarevic-stepstone-job-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
}
},
"components": {
"schemas": {
"inputSchema": {
"type": "object",
"required": [
"startUrls"
],
"properties": {
"startUrls": {
"title": "Start URLs",
"type": "array",
"description": "Stepstone.de search URLs (e.g., https://www.stepstone.de/jobs/ai?page=2&searchOrigin=Homepage_top-search)",
"items": {
"type": "object",
"required": [
"url"
],
"properties": {
"url": {
"type": "string",
"title": "URL of a web page",
"format": "uri"
}
}
}
},
"maxItems": {
"title": "Max Items to Scrape",
"minimum": 0,
"type": "integer",
"description": "Maximum number of listings to collect. Set to 0 for unlimited.",
"default": 10
},
"proxy": {
"title": "Proxy configuration",
"type": "object",
"description": "Residential proxies are mandatory for Funda to avoid blocks and interstitials.",
"default": {
"useApifyProxy": true,
"apifyProxyGroups": [
"RESIDENTIAL"
]
}
}
}
},
"runsResponseSchema": {
"type": "object",
"properties": {
"data": {
"type": "object",
"properties": {
"id": {
"type": "string"
},
"actId": {
"type": "string"
},
"userId": {
"type": "string"
},
"startedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"finishedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"status": {
"type": "string",
"example": "READY"
},
"meta": {
"type": "object",
"properties": {
"origin": {
"type": "string",
"example": "API"
},
"userAgent": {
"type": "string"
}
}
},
"stats": {
"type": "object",
"properties": {
"inputBodyLen": {
"type": "integer",
"example": 2000
},
"rebootCount": {
"type": "integer",
"example": 0
},
"restartCount": {
"type": "integer",
"example": 0
},
"resurrectCount": {
"type": "integer",
"example": 0
},
"computeUnits": {
"type": "integer",
"example": 0
}
}
},
"options": {
"type": "object",
"properties": {
"build": {
"type": "string",
"example": "latest"
},
"timeoutSecs": {
"type": "integer",
"example": 300
},
"memoryMbytes": {
"type": "integer",
"example": 1024
},
"diskMbytes": {
"type": "integer",
"example": 2048
}
}
},
"buildId": {
"type": "string"
},
"defaultKeyValueStoreId": {
"type": "string"
},
"defaultDatasetId": {
"type": "string"
},
"defaultRequestQueueId": {
"type": "string"
},
"buildNumber": {
"type": "string",
"example": "1.0.0"
},
"containerUrl": {
"type": "string"
},
"usage": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "integer",
"example": 1
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
},
"usageTotalUsd": {
"type": "number",
"example": 0.00005
},
"usageUsd": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "number",
"example": 0.00005
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
}
}
}
}
}
}
}
}
```