GermanTechJobs Scraper: Salary & Tech Stack

What does GermanTechJobs Scraper do?

GermanTechJobs Scraper extracts structured tech-job listings from germantechjobs.de, Germany's salary-transparent IT job board — every posting carries a salary range, the full tech stack, required seniority and company details, one row per job. Filter by technology, seniority, salary, company size and visa sponsorship, and run incrementally to return only new and changed jobs.

How to use this actor

• 👉 Register for a free Apify account — no credit card required.
• 🎉 Just click Sign up free on Apify → and complete a quick signup.
• 💰 A free Apify account includes $5 in monthly credits — enough to test this actor.
• ⏳ Scrape during the free trial, with no commitment or upfront payment required.

Key features

• 💰 Structured salary — germanTechJobs mandates a salary range on every posting, so every record ships structured salaryMin / salaryMax / salaryCurrency (EUR) / salaryType (yearly) — never a hidden or "competitive" salary to parse around. Filter by minSalary to skip everything below your band.
• 🧰 Full tech-role schema — every listing ships a normalized tech stack (technologies[]), seniority (experienceLevel), workplace mode (office / remote / hybrid), and a visa-sponsorship flag — parsed into typed fields, not buried in the description. Filter a run by technologies, remoteOnly, or minSalary.
• ♻️ Incremental mode — recurring runs emit only NEW / UPDATED / REAPPEARED records — UNCHANGED and EXPIRED are opt-in. First run builds the baseline; subsequent runs emit and charge only for the diff. Pair with notifications for daily "new jobs" alerts to your hiring team. Saves 80–95% on daily monitoring.
• 🔔 Notifications — Telegram, Slack, Discord, WhatsApp Cloud API, generic webhook — out of the box. Pair with incremental + notifyOnlyChanges for daily "new Germantechjobs jobs" pings to your hiring channel.
• 📧 Email + phone extraction — every record carries extractedEmails[] and extractedPhones[] regex-pulled from the description — direct-outreach lists with no extra processing step.
• 🎯 Batch searches — batch ["python developer", "data engineer", "ML engineer"] in one run — one dedup state across all searches, single dataset, one Actor-Start charge instead of N.
• 📦 Compact mode — AI-agent and MCP-friendly compact payloads with core fields only — pipe straight into your ATS, salary-benchmarking tool, or LLM context without parsing extras.
• 🔌 MCP connectors — export your results into Notion via Apify's MCP connectors — a clean run-summary page, no glue code. Opt-in via the App connector field; deterministic field-mapping, no AI. Built on Apify's connector framework, so more destinations open up as their catalog grows.

What data can you extract from germantechjobs.de?

Each result includes Core job fields (jobId, jobKey, title, location, postalCode, latitude, longitude, and requirements, and more), detail fields when enrichment is enabled (description, descriptionText, descriptionHtml, descriptionMarkdown, and descriptionLength), apply information (applyUrl), and company metadata (company, companyType, companyLogo, and companyUrl). 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 and company metadata 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 — Optional keyword filter, matched on title / company / tech stack / description. Leave empty to return the whole board. Use a JSON array for multiple keywords.
• country — Which germantechjobs.de market to search. (default: "DE")
• location — Optional city filter (e.g. "Berlin"), matched on the job's city. Use a JSON array for multiple cities.
• technologies — Optional. Keep only jobs whose tech stack includes any of these (e.g. ["React","AWS"]). Case-insensitive.
• remoteOnly — Keep only jobs whose workplace is remote or hybrid. (default: false)
• minSalary — Optional. Keep only jobs whose upper salary is at least this. 0 = no minimum. GermanTechJobs mandates a salary range on every posting. (default: 0)
• jobType — Optional. Keep only jobs of this employment type. (default: "")
• expLevel — Optional. Keep only jobs at this experience level. (default: "")
• companySize — Optional. Keep only jobs at companies of this headcount band. (default: "")
• companyType — Optional. Keep only jobs at this type of company. (default: "")
• language — Optional. Keep only jobs whose posting language matches. (default: "")
• visaSponsorshipOnly — Keep only jobs that offer visa sponsorship. (default: false)
• ...and 26 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 engineer",
  "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 engineer",
  "maxResults": 200,
  "incrementalMode": true,
  "stateKey": "software-engineer-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 engineer",
  "jobType": "Full-Time",
  "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": "fd2d620bc66e26ea952d31cbaf47ce52557326df0d554a0d8af2d9ca594643e4",
  "jobKey": "Deutsche-Bundesbank-Duales-Studium-Angewandte-Informatik",
  "title": "Duales Studium Angewandte Informatik",
  "company": "Deutsche Bundesbank",
  "companyType": "Product",
  "companyLogo": "https://jobg8-g8h5gsazefe0ehc4.z03.azurefd.net/joblogos/2706396.png",
  "companyUrl": "https://germantechjobs.de/company/deutsche-bundesbank",
  "companyEmployeeRange": "5k+",
  "location": "Mainz",
  "postalCode": "55122",
  "latitude": 49.99537865,
  "longitude": 8.22610186,
  "description": "Wir sind die Deutsche Bundesbank und als Zentralbank sorgen wir für einen stabilen Euro und sichere Finanzmärkte. Damit leisten wir einen wichtigen Beitrag für die Gesellschaft in Deutschland und Euro...",
  "descriptionText": "Wir sind die Deutsche Bundesbank und als Zentralbank sorgen wir für einen stabilen Euro und sichere Finanzmärkte. Damit leisten wir einen wichtigen Beitrag für die Gesellschaft in Deutschland und Euro...",
  "descriptionHtml": "<p>Wir sind die Deutsche Bundesbank und als Zentralbank sorgen wir für einen stabilen Euro und sichere Finanzmärkte. Damit leisten wir einen wichtigen Beitrag für die Gesellschaft in Deutschland und E...",
  "descriptionMarkdown": "Wir sind die Deutsche Bundesbank und als Zentralbank sorgen wir für einen stabilen Euro und sichere Finanzmärkte. Damit leisten wir einen wichtigen Beitrag für die Gesellschaft in Deutschland und Euro...",
  "descriptionLength": 1914,
  "requirements": "- Hochschulzugangsberechtigung\n- Ausgeprägte konzeptionelle und analytische Fähigkeiten, nachgewiesen durch das Bestehen unseres Eignungstests\n- Gute Englischkenntnisse, nachgewiesen durch das Bestehe...",
  "responsibilities": "- Wir vermitteln dir in den Theoriephasen umfangreiches IT-Fachwissen, insbesondere in den Bereichen Programmierung, Webtechnologien, Datenbanken und IT-Infrastrukturen.\n- Wir ermöglichen dir, deine S...",
  "language": "German",
  "salaryText": "€14,400 / year",
  "salaryMin": 14400,
  "salaryMax": 14400,
  "salaryCurrency": "EUR",
  "salaryType": "yearly",
  "employmentType": "Internship",
  "experienceLevel": "Junior",
  "workplace": "office",
  "visaSponsorship": false,
  "techCategory": "IT",
  "postedAt": "2026-05-23T09:55:00.396Z",
  "updatedAt": "2026-07-16T22:47:53.489Z",
  "canonicalUrl": "https://germantechjobs.de/jobs/Deutsche-Bundesbank-Duales-Studium-Angewandte-Informatik",
  "applyUrl": "https://www.jobg8.com/Traffic.aspx?l75L%2fGCuXfqEuVcrWpB7pYzxUdhqPITIi",
  "sourceUrl": "https://germantechjobs.de/jobs/Deutsche-Bundesbank-Duales-Studium-Angewandte-Informatik",
  "sourceCountry": "DE",
  "sourceDomain": "germantechjobs.de",
  "searchQuery": "germantechjobs.de",
  "searchUrl": "https://germantechjobs.de/rss",
  "isSponsored": true,
  "scrapedAt": "2026-07-16T22:59:31.288Z",
  "fetchedAt": "2026-07-16T22:59:31.288Z",
  "detailFetched": true,
  "contentQuality": "full",
  "contentHash": "sha256..."
}

Incremental fields

When incremental mode is on, each record also carries:

• changeType — one of NEW, UPDATED, UNCHANGED, REAPPEARED, EXPIRED. Default output covers NEW / UPDATED / REAPPEARED; set emitUnchanged: true or emitExpired: true to opt into the others.
• firstSeenAt, lastSeenAt — ISO-8601 timestamps tracking the listing across runs.
• isRepost, repostOfId, repostDetectedAt — populated when a new listing matches the tracked content of a previously expired one. Set skipReposts: true to drop detected reposts from the output.

How to scrape germantechjobs.de

1. Go to GermanTechJobs 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, 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 germantechjobs.de for market research and competitive analysis.
• Track salary trends across regions and categories over time.
• Monitor new and changed jobs on scheduled runs without processing the full dataset every time.
• Auto-apply or feed apply URLs into your ATS / hiring pipeline.
• 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 germantechjobs.de?

GermanTechJobs 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: $0.005 per run
• Per result: $0.0015 per job record

Example costs:

• 10 results: $0.02
• 25 results: $0.042
• 100 results: $0.15
• 200 results: $0.3
• 500 results: $0.76

Example: recurring monitoring savings

These examples compare full re-scrapes with incremental runs at different churn rates. Churn is the share of jobs 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 rate	Full re-scrape run cost	Incremental run cost	Savings vs full re-scrape	Monthly cost after baseline
5% — stable niche query	$0.15	$0.01	$0.14 (92%)	$0.38
15% — moderate broad query	$0.15	$0.03	$0.13 (82%)	$0.82
30% — high-volume aggregator	$0.15	$0.05	$0.11 (68%)	$1.50

Full re-scrape monthly cost at daily polling: $4.65. First month with incremental costs $0.52 / $0.95 / $1.60 for the 5% / 15% / 30% scenarios because the first run builds baseline state at full cost before incremental savings apply.

Platform usage is included in the per-result fee shown above.

FAQ

How many results can I get from germantechjobs.de?

The number of results depends on the search query and available jobs on germantechjobs.de. Use the maxResults parameter to control how many results are returned per run.

Does GermanTechJobs Scraper support recurring monitoring?

Yes. Enable incremental mode to only receive new or changed jobs 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 GermanTechJobs Scraper with other apps?

Yes. GermanTechJobs 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 GermanTechJobs 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 GermanTechJobs Scraper through an MCP Server?

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

Is it legal to scrape germantechjobs.de?

This actor extracts publicly available data from germantechjobs.de. 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

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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

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