StepStone DK Scraper - Denmark Jobs avatar

StepStone DK Scraper - Denmark Jobs

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StepStone DK Scraper - Denmark Jobs

StepStone DK Scraper - Denmark Jobs

Scrape stepstone.dk - Denmark’s management and specialist job portal. Salary data, employer profiles, and employment type filters. Incremental mode detects new and changed listings. Compact output for AI agents and MCP workflows.

Pricing

from $2.00 / 1,000 results

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Black Falcon Data

Black Falcon Data

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14 hours ago

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What does StepStone DK Scraper do?

StepStone DK Scraper extracts structured job data from stepstone.dk — including salary data, contact details, company metadata, full descriptions, remote-work indicators, and location data. It supports keyword search, location filters, and controllable result limits, so you can run the same query consistently over time. The actor also offers detail enrichment (full descriptions, company metadata, and contact information) where the source provides them.

Key features

  • Incremental mode — recurring runs emit and charge only for listings that are new or whose tracked content changed. First run builds the baseline state; subsequent runs emit only new or changed records.
  • Detail enrichment — full descriptions, company metadata, and contact information where the source provides them.
  • Compact mode — AI-agent and MCP-friendly payloads with core fields only.

What data can you extract from stepstone.dk?

Each result includes Core listing fields (jobId, tid, title, location, fullAddress, city, zipCode, and latitude, and more), detail fields when enrichment is enabled (description), contact and apply information (applyUrl, contactEmail, and contactPhone), and company metadata (company, workplaceCompany, companyLogoUrl, and companyWebsite). In standard mode, all fields are always present — unavailable data points are returned as null, never omitted. In compact mode, only core fields are returned.

Enable detail enrichment in the input to get richer fields such as full descriptions, company metadata, and contact information where the source provides them.

Input

The main inputs are a search keyword, an optional location filter, and a result limit. Additional filters and options are available in the input schema.

Key parameters:

  • query — Job search keywords (e.g. 'software engineer', 'projektleder').
  • location — Free-text location (city or area name). Use Region for structured filtering.
  • region — Filter by Danish region or area.
  • employmentType — Filter by employment type.
  • remoteWork — Filter by remote work availability.
  • workingHours — Filter by working hours type.
  • jobAge — Only show jobs posted within this period.
  • maxResults — Maximum total results (0 = unlimited). (default: 25)
  • includeDetails — Fetch full job descriptions from detail pages. Slower but provides complete descriptions. (default: false)
  • descriptionMaxLength — Truncate description to N characters. 0 = no truncation. (default: 0)
  • compact — Core fields only (for AI-agent/MCP workflows). (default: false)
  • incrementalMode — Only output new/changed jobs compared to previous run. (default: false)
  • ...and 1 more parameters

Input examples

Basic search — Keyword-driven search with a result cap.

→ Full payload per result — all standard fields populated where the source provides them.

{
"query": "software",
"maxResults": 50
}

Incremental tracking — Only emit jobs that changed since the previous run with this stateKey.

→ First run builds the baseline state. Subsequent runs emit only records that are new or whose tracked content changed. Set emitUnchanged: true to include unchanged records as well.

{
"query": "software",
"maxResults": 200,
"incrementalMode": true,
"stateKey": "software-tracker"
}

Compact filtered output — Combine filters with compact mode for a lightweight AI-agent or MCP data source.

→ Core fields only — ideal for piping into LLMs or downstream tools without token overhead.

{
"query": "software",
"employmentType": "permanent",
"maxResults": 50,
"compact": true
}

Output

Each run produces a dataset of structured job records. Results can be downloaded as JSON, CSV, or Excel from the Dataset tab in Apify Console.

Example job record

{
"jobId": "8eddb3138d2be78639ebce196eed6fe30d9d05e3a55dd741f1d61cd1fe1b25d8",
"tid": "h1647246",
"title": "Technical Lead",
"company": "PC SCHEMATIC A/S",
"workplaceCompany": "PC SCHEMATIC A/S",
"location": "Roskilde",
"fullAddress": "Gammel Marbjergvej 15, 4000 Roskilde",
"city": "Roskilde",
"zipCode": "4000",
"latitude": 55.6470652,
"longitude": 12.1407991,
"description": "Do you want to lead the technical development of the electrical automation software of the future?\n\nWe are looking for a Technical Lead to join our development team.\n\nAre you an experienced developer...",
"employmentType": "Permanent",
"workingHours": "Full-time",
"remoteWork": false,
"remoteWorkLabel": "Possible",
"postedDate": "2026-03-13",
"expiresDate": "2026-04-10",
"applicationDeadline": null,
"applyUrl": "https://www.stepstone.dk/c?t=h1647246&ctx=w&jobsearch_position=1&jobsearchid=1046499114",
"url": "https://www.stepstone.dk/jobannonce/h1647246/technical-lead",
"portalUrl": "https://www.stepstone.dk",
"companyLogoUrl": "https://www.stepstone.dk/img/logo/pc_scematic_600x314_20260312.png",
"companyWebsite": "http://www.pcschematic.com/DA/",
"contactEmail": "kirsten.moeller@pcschematic.com",
"contactPhone": "2384 5296",
"salaryText": null,
"scrapedAt": "2026-03-28T08:55:45.482Z",
"source": "stepstone.dk"
}

Incremental fields

When incremental: true, each record also carries:

  • changeType — one of NEW, UPDATED, UNCHANGED, REAPPEARED, EXPIRED.
  • firstSeenAt, lastSeenAt — ISO-8601 timestamps tracking the listing across runs.

How to scrape stepstone.dk

  1. Go to StepStone DK Scraper in Apify Console.
  2. Enter a search keyword and optional location filter.
  3. Set maxResults to control how many results you need.
  4. Enable includeDetails if you need full descriptions, contact info, or company data.
  5. Click Start and wait for the run to finish.
  6. Export the dataset as JSON, CSV, or Excel.

Use cases

  • Extract job data from stepstone.dk for market research and competitive analysis.
  • Track salary trends across regions and categories over time.
  • Monitor new and changed listings on scheduled runs without processing the full dataset every time.
  • Build outreach lists using contact details and apply URLs from listings.
  • Research company hiring patterns, employer profiles, and industry distribution.
  • Use structured location data for regional analysis, mapping, and geo-targeting.
  • Feed structured data into AI agents, MCP tools, and automated pipelines using compact mode.
  • Export clean, structured data to dashboards, spreadsheets, or data warehouses.

How much does it cost to scrape stepstone.dk?

StepStone DK Scraper uses pay-per-event pricing. You pay a small fee when the run starts and then for each result that is actually produced.

  • Run start: $0.01 per run
  • Per result: $0.002 per job record

Example costs:

  • 10 results: $0.03
  • 100 results: $0.21
  • 500 results: $1.01

Example: recurring monitoring savings

These examples compare full re-scrapes with incremental runs at different churn rates. Churn is the share of listings that are new or whose tracked content changed since the previous run. Actual churn depends on your query breadth, source activity, and polling frequency — the scenarios below are examples, not predictions.

Example setup: 100 results per run, daily polling (30 runs/month). Event-pricing examples scale linearly with result count.

Churn rateFull re-scrape run costIncremental run costSavings vs full re-scrapeMonthly cost after baseline
5% — stable niche query$0.21$0.02$0.19 (90%)$0.60
15% — moderate broad query$0.21$0.04$0.17 (81%)$1.20
30% — high-volume aggregator$0.21$0.07$0.14 (67%)$2.10

Full re-scrape monthly cost at daily polling: $6.30. First month with incremental costs $0.79 / $1.37 / $2.24 for the 5% / 15% / 30% scenarios because the first run builds baseline state at full cost before incremental savings apply.

FAQ

How many results can I get from stepstone.dk?

The number of results depends on the search query and available listings on stepstone.dk. Use the maxResults parameter to control how many results are returned per run.

Does StepStone DK Scraper support recurring monitoring?

Yes. Enable incremental mode to only receive new or changed listings on subsequent runs. This is ideal for scheduled monitoring where you want to track changes over time without re-processing the full dataset.

Can I integrate StepStone DK Scraper with other apps?

Yes. StepStone DK Scraper works with Apify's integrations to connect with tools like Zapier, Make, Google Sheets, Slack, and more. You can also use webhooks to trigger actions when a run completes.

Can I use StepStone DK Scraper with the Apify API?

Yes. You can start runs, manage inputs, and retrieve results programmatically through the Apify API. Client libraries are available for JavaScript, Python, and other languages.

Can I use StepStone DK Scraper through an MCP Server?

Yes. Apify provides an MCP Server that lets AI assistants and agents call this actor directly. Use compact mode and descriptionMaxLength to keep payloads manageable for LLM context windows.

This actor extracts publicly available data from stepstone.dk. Web scraping of public information is generally considered legal, but you should always review the target site's terms of service and ensure your use case complies with applicable laws and regulations, including GDPR where relevant.

Your feedback

If you have questions, need a feature, or found a bug, please open an issue on the actor's page in Apify Console. Your feedback helps us improve.

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Getting started with Apify

New to Apify? Create a free account with $5 credit — no credit card required.

  1. Sign up — $5 platform credit included
  2. Open this actor and configure your input
  3. Click Start — export results as JSON, CSV, or Excel

Need more later? See Apify pricing.