StepStone Jobs Scraper

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

{
  "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:

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

Advanced request:

{
  "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.

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 — company details for employer research alongside job listings.
• 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.