We extract job postings, employer profiles, salary estimates, and geographical distribution metrics from stepstone.de. Delivered as clean JSON, CSV, or Parquet to S3 or BigQuery on your schedule.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Job Postings objects from stepstone.de. All fields typed and schema-versioned.
"job_id": "8947210", "title": "Senior Data Engineer (m/w/d)", "company_name": "TechLogix GmbH", "location": "Berlin", "contract_type": "Vollzeit", "work_model": "Hybrid", "salary_min": 75000, "salary_max": 95000, "posted_date": "2026-05-10"
| # | job_id | title | company_name | location | contract_type | work_model |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Company Profiles objects from stepstone.de. All fields typed and schema-versioned.
"company_id": "C-4921", "name": "TechLogix GmbH", "industry": "IT-Dienstleistungen", "size": "501-1000", "headquarters": "Berlin", "rating": 4.2, "active_jobs_count": 47, "website": "https://techlogix.de"
| # | company_id | name | industry | size | website | headquarters |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Salary Data objects from stepstone.de. All fields typed and schema-versioned.
"job_title": "Data Engineer", "location": "München", "experience_level": "Senior", "base_salary": 85000, "total_compensation": 92000, "data_points_count": 124, "confidence_score": "High", "currency": "EUR"
| # | job_title | location | experience_level | base_salary | bonus | total_compensation |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Search Results objects from stepstone.de. All fields typed and schema-versioned.
"keyword": "Python Developer", "location": "Hamburg", "rank": 1, "job_id": "8931024", "title": "Python Backend Developer", "company": "HanseTech", "promoted_flag": true, "easy_apply_flag": false
| # | keyword | location | rank | job_id | title | company |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Skill Requirements objects from stepstone.de. All fields typed and schema-versioned.
"job_id": "8947210", "hard_skills": "['Python', 'SQL', 'AWS']", "soft_skills": "['Kommunikation', 'Teamfähigkeit']", "languages": "['Deutsch', 'Englisch']", "education_level": "Bachelor", "years_experience": "3-5 Jahre", "tools_software": "['Docker', 'Kubernetes', 'Airflow']"
| # | job_id | title | hard_skills | soft_skills | languages | education_level |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Our Stepstone scraper navigates search pagination, dynamic job descriptions, and salary estimates while bypassing strict anti-bot measures to deliver structured DACH labour data.
Extract complete job texts, including requirements, responsibilities, benefits, and company descriptions, parsed into structured fields.
Scrape Stepstone Gehaltsplaner data and job-specific salary ranges, including minimum, maximum, and median figures.
Extract employer profiles, including industry, employee count, headquarters location, and aggregated employee ratings.
Capture precise job locations, hybrid work models, and fully remote flags to map geographical hiring trends.
Track exact posting dates and active duration to calculate time-to-hire metrics and vacancy ageing.
Monitor job search rankings for specific titles or skills, differentiating between organic listings and promoted placements.
Isolate programming languages, certifications, and soft skills from unstructured job descriptions using regex and NLP.
Run daily diffs to capture only new job postings, modified listings, or removed vacancies without re-downloading the entire catalogue.
Bypass Stepstone's Datadome and Cloudflare protections using residential German IP proxies and headless browser fingerprinting.
Brief in. Clean data out.
Specify target keywords, locations, industries, or specific company IDs. We map the extraction schema to your requirements.
We configure Playwright crawlers, German residential proxy rotation, and session management to navigate stepstone.de.
We test data completeness, verify salary extraction accuracy, and ensure location fields are correctly normalised.
Clean JSON, CSV, or Parquet files delivered to your AWS S3 bucket or Snowflake instance on a daily or weekly schedule.
Job boards protect their listings aggressively. Here is how we maintain stable extraction pipelines against strict mitigation systems.
Stepstone uses advanced bot protection that flags data centre IPs and headless browsers. We route requests through German residential proxies and use Playwright with stealth plugins to mimic legitimate user behaviour.
Job descriptions and salary widgets on Stepstone are rendered client-side. We execute full JavaScript sessions to ensure all dynamic elements, including hidden contact details and expandable text blocks, are captured.
Search results are capped at a specific number of pages. We use granular geographic and keyword filtering to break down large queries, ensuring we extract the entire catalogue without hitting pagination walls.
Employers format job postings differently. We apply post-processing to normalise contract types, standardise location names, and extract specific data points like salary ranges from free-text descriptions.
We maintain a database of active job IDs. By comparing current runs against historical state, we accurately report when a job is closed or modified, providing precise time-to-fill metrics.
Economic researchers and analysts track hiring volume, skill demand, and salary trends across the DACH region.
Enterprises monitor rival hiring activity to deduce strategic shifts, expansion plans, and technology stack adoption.
HR departments use aggregated salary estimates to ensure their compensation packages remain competitive in specific regions.
Sales teams identify companies actively hiring for specific roles (e.g., IT Directors) as a signal for software or service procurement.
Niche job portals supplement their own inventory by aggregating relevant listings from Stepstone.
Analysts correlate job location data and remote work trends with commercial real estate demand and urban migration patterns.
"Stepstone.de holds the most accurate pulse on the DACH region's labour market, but extracting that intelligence requires bypassing aggressive bot mitigation."
Job boards deploy heavy anti-scraping measures to protect their primary asset. Reliable Stepstone extraction demands residential proxies, JavaScript rendering, and constant DOM monitoring. DataFlirt manages this infrastructure entirely, delivering structured labour market intelligence straight to your warehouse.
Everything supported by our stepstone.de scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy manages orchestration and retry logic, while Playwright handles JavaScript execution to render Stepstone's dynamic job descriptions and salary widgets.
We maintain pools of German residential ISP proxies. Rotation happens per-request to mimic local user traffic and bypass geographic rate limits.
Pipelines run on Kubernetes clusters. Airflow handles scheduling for daily job diffs, ensuring data freshness. All state is stored in managed PostgreSQL.
Data delivered to where your team already works — no new tooling required.
About stepstone.de scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available job postings is generally permissible. DataFlirt extracts only public, non-authenticated job and company data. We do not access candidate profiles, CVs, or bypass authentication walls. Clients should consult legal counsel regarding their specific data usage.
We utilise German residential proxies, headless browsers with realistic fingerprints, and randomised request intervals. This approach effectively navigates Datadome and Cloudflare protections without triggering blocks.
Yes. When employers do not list a salary, Stepstone often provides an estimated range via their Gehaltsplaner feature. We extract this estimate alongside the job posting.
Most clients opt for daily updates to track new postings and removed vacancies. We can configure pipelines for hourly runs if you require near real-time alerts for specific keywords.
Yes. We also build pipelines for Xing, LinkedIn, Indeed.de, and regional portals to provide comprehensive coverage of the German-speaking labour market.
Yes. We provide a sample dataset of up to 1,000 job postings based on your target criteria during the scoping phase, allowing you to validate the schema and data quality.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a daily feed of IT roles in Berlin or a comprehensive dump of DACH salary data — we build and operate the pipeline. Tell us your requirements.
