We extract job listings, company profiles, salary estimates, and skill requirements from Careerbuilder. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.
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 careerbuilder.com. All fields typed and schema-versioned.
"job_id": "J3V1D86H8Z8N9Y2P", "title": "Senior Data Engineer", "company_name": "TechLogix Solutions", "location": "Chicago, IL", "remote_flag": true, "salary_min": 130000, "salary_max": 160000, "posted_date": "2026-05-10T08:30:00Z"
| # | job_id | title | company_name | location | employment_type | remote_flag |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Company Profiles objects from careerbuilder.com. All fields typed and schema-versioned.
"company_id": "C8B9X2M4Q1L7", "name": "TechLogix Solutions", "industry": "Information Technology", "company_size": "501 to 1000", "headquarters": "Chicago, IL", "active_jobs_count": 42, "founded_year": 2012
| # | company_id | name | industry | company_size | website_url | headquarters |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Salary Data objects from careerbuilder.com. All fields typed and schema-versioned.
"job_title": "Senior Data Engineer", "location": "Chicago, IL", "base_salary": 145000, "bonus": 15000, "total_compensation": 160000, "currency": "USD", "pay_period": "ANNUAL", "confidence_score": 0.88
| # | job_title | location | company_name | base_salary | bonus | total_compensation |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Skill Requirements objects from careerbuilder.com. All fields typed and schema-versioned.
"job_id": "J3V1D86H8Z8N9Y2P", "skill_name": "Apache Airflow", "required_flag": true, "experience_years": 3, "category": "Orchestration", "certification_needed": false, "priority": "HIGH"
| # | job_id | skill_name | required_flag | experience_years | category | certification_needed |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Search Results objects from careerbuilder.com. All fields typed and schema-versioned.
"keyword": "data engineer", "location_query": "Chicago, IL", "position": 1, "job_id": "J3V1D86H8Z8N9Y2P", "sponsored_flag": false, "posted_time_ago": "2 hours ago", "scraped_at": "2026-05-12T09:14:33Z"
| # | keyword | location_query | position | job_id | title | company_name |
|---|---|---|---|---|---|---|
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Our Careerbuilder scraper extracts structured job details, employer profiles, and salary estimates while handling pagination, dynamic content loading, and bot protection mechanisms.
Title, description, location, employment type, and salary bands extracted at the individual job posting level.
Capture employer details including industry category, headcount estimates, headquarters location, and active job counts.
Extract posted salary ranges, hourly rates, and compensation types directly from search results and job details.
Parse unstructured job descriptions to isolate specific technical skills, required certifications, and experience levels.
Identify workplace policies accurately by checking metadata and parsing the job description text for remote indicators.
Track organic versus sponsored job placements for specific keywords and locations over time.
Scrape jobs across multiple city and state combinations using a unified location configuration.
Run continuous pipelines that detect new job postings and flag closed or expired listings automatically.
Follow outbound application links to identify the underlying Applicant Tracking System used by the employer.
Brief in. Clean data out.
Provide keywords, location lists, or specific company names. We design the extraction schema together.
We configure Scrapy and Playwright crawlers, proxy rotation, and session management for careerbuilder.com.
Schema validation, null-rate checks, and location parsing accuracy validation before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Job boards deploy strict rate limits and dynamic rendering. Here is how we maintain stable extraction pipelines.
Careerbuilder uses advanced bot detection. Our crawlers use residential ISP proxies with realistic browser fingerprints and full cookie session management trained on human browsing patterns.
Job search results and pagination rely heavily on JavaScript. We run full Playwright browser sessions to trigger lazy-loading and capture data that headless HTTP clients miss entirely.
Job descriptions vary wildly by employer. Our extraction logic uses fallback chains and regex pattern matching to reliably isolate salaries, skills, and remote work policies from free-text fields.
We maintain a hash index of active job IDs. Subsequent runs identify newly posted jobs and flag missing IDs as closed listings, reducing downstream processing load.
Every run emits structured logs to our observability stack. We alert on null-rate spikes or sudden drops in job counts to ensure data continuity.
Economists and research firms track hiring volume, salary trends, and skill demand across specific regions and industries.
Corporate strategy teams monitor competitor job postings to infer strategic shifts, new product developments, or expansion plans.
HR departments aggregate compensation data to ensure their internal salary bands remain competitive in local markets.
Niche job boards and career portals backfill their platforms with targeted listings filtered by specific industries or remote status.
EdTech companies analyse required skills in emerging job categories to design relevant curriculum and certification programs.
Sales teams identify companies actively hiring for specific roles to time their outreach for software or recruitment services.
"Careerbuilder holds a massive repository of active hiring intent and salary benchmarking data, but accessing it systematically requires a dedicated pipeline."
Extracting job market data at volume requires navigating anti-bot protections, standardising unstructured job descriptions, and mapping complex location hierarchies. DataFlirt manages the extraction infrastructure so your data science team can focus on labour market analysis rather than proxy rotation.
Everything supported by our careerbuilder.com 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 handles crawl orchestration and deduplication. Playwright handles JavaScript rendering and interaction flows. Combined via scrapy-playwright middleware.
We maintain pools of residential ISP proxies. Rotation happens per-request with sticky sessions where required to prevent IP bans.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling and dependency management. All state is stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About careerbuilder.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available job postings is generally permissible. DataFlirt targets only public, non-authenticated job and company data. We do not extract personal candidate data or circumvent employer authentication walls.
We use residential ISP proxies, full Playwright browser sessions, and request timing modelled on human behaviour to maintain stable access and bypass rate limits.
Yes. We configure pipelines to iterate through specific city, state, or postal code lists to ensure comprehensive geographic coverage.
Pipelines can be configured for daily or sub-daily runs to capture new job postings quickly and accurately reflect the current active market.
Yes. By maintaining an index of active job IDs, we can emit a status update when a previously active job no longer appears in search results or returns a closed status page.
Yes. We provide a sample run of up to 500 job listings based on your target keywords and locations to validate schema fit before contracting.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off export of industry salaries or a continuous feed of competitor job postings, we build and operate the pipeline. Tell us what you need.
