Extract job listings, department hierarchies, location data, and company metadata from SmartRecruiters ATS portals. 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 smartrecruiters.com. All fields typed and schema-versioned.
"job_id": "743999812345678", "title": "Senior Backend Engineer", "company_name": "TechCorp Global", "location": "Bengaluru, Karnataka, India", "department": "Engineering", "employment_type": "Full-time", "remote_tier": "Hybrid", "posted_date": "2026-05-10T14:30:00Z"
| # | job_id | title | company_name | location | department | employment_type |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Company Metadata objects from smartrecruiters.com. All fields typed and schema-versioned.
"company_id": "TCG992", "name": "TechCorp Global", "industry": "Enterprise Software", "website": "https://techcorpglobal.example.com", "active_jobs_count": 142, "headquarters": "San Francisco, CA", "careers_url": "https://jobs.smartrecruiters.com/TechCorpGlobal"
| # | company_id | name | industry | website | logo_url | active_jobs_count |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Job Requirements objects from smartrecruiters.com. All fields typed and schema-versioned.
"job_id": "743999812345678", "experience_level": "Mid-Senior level", "education": "Bachelor's Degree", "skills": "['Python', 'PostgreSQL', 'System Design']", "language": "English", "certifications": "['AWS Certified Solutions Architect']", "qualifications": "5+ years of backend development experience."
| # | job_id | experience_level | education | skills | qualifications | responsibilities |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Location Data objects from smartrecruiters.com. All fields typed and schema-versioned.
"job_id": "743999812345678", "city": "Bengaluru", "state": "Karnataka", "country": "India", "remote_status": "Hybrid", "lat": 12.9716, "lng": 77.5946
| # | job_id | city | state | country | postal_code | remote_status |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Application Details objects from smartrecruiters.com. All fields typed and schema-versioned.
"job_id": "743999812345678", "apply_url": "https://jobs.smartrecruiters.com/TechCorpGlobal/743999812345678/apply", "requires_resume": true, "portal_type": "Standard", "eeo_statement": true, "custom_questions": "['Do you require visa sponsorship?']"
| # | job_id | apply_url | requires_resume | custom_questions | compliance_fields | eeo_statement |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
SmartRecruiters powers hiring for thousands of companies. We handle the discovery, pagination, JavaScript rendering, and normalisation across diverse company portals to deliver clean job records.
Map and index active job listings across thousands of individual company portals hosted on the SmartRecruiters ATS infrastructure.
Extract raw HTML or clean text for job descriptions, parsing out responsibilities, requirements, and benefits into structured fields.
Standardise city, state, and country fields across different company input formats, including remote and hybrid tier categorisation.
Monitor portals for removed listings. We emit diffs when jobs are closed or filled, keeping your database accurate.
Navigate infinite scroll and API pagination patterns across complex corporate career pages without missing records.
Capture the internal company taxonomy for roles, mapping jobs to their respective divisions, departments, and teams.
Extract the exact application endpoint for every listing, bypassing intermediate landing pages and tracking redirects.
Run pipelines at daily or hourly cadences to capture new roles the moment they are published by recruitment teams.
Bypass rate limits and firewall protections on custom-domain ATS portals using residential proxies and TLS fingerprinting.
Brief in. Clean data out.
Provide a list of target companies, industries, or specific SmartRecruiters portal URLs. We map the extraction schema.
We configure Scrapy crawlers, proxy rotation, and pagination logic to handle ATS portal variations.
Schema validation, null-rate checks, and location normalisation rules are applied before full execution.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on schedule.
Extracting data from an ATS platform requires navigating thousands of distinct configurations. Here is how we maintain stability.
Many companies map their SmartRecruiters ATS to custom subdomains (e.g., careers.company.com). Our crawlers resolve the underlying ATS endpoints and normalise the data extraction regardless of the front-end domain.
SmartRecruiters portals heavily utilise undocumented internal APIs to load job data. We intercept these XHR requests to extract clean JSON payloads directly, reducing reliance on fragile DOM parsing.
Different companies configure their ATS fields differently. Our normalisation layer maps custom company fields into a unified schema, ensuring your downstream pipeline receives consistent data structures.
Job boards change rapidly. We maintain a hash index of active jobs. When a job drops from the portal, our pipeline emits a deletion record, ensuring your database accurately reflects open headcount.
Scraping thousands of jobs from a single company portal triggers rate limits. We distribute requests across residential proxy pools with randomised delays to maintain high throughput without blocks.
Economic research firms aggregate job postings to track hiring trends, skill demand, and remote work shifts across industries.
Corporate strategy teams monitor competitor career pages to identify strategic investments, expansion plans, and technology adoption.
Niche job boards and aggregators backfill their platforms with targeted roles extracted directly from employer ATS portals.
B2B sales teams use open roles as buying signals. A company hiring five Salesforce developers is a prime target for SaaS tooling.
HR tech platforms extract location and salary data to build compensation models and benchmark industry pay bands.
Machine learning teams use structured job descriptions and requirements to train candidate matching and resume parsing models.
"SmartRecruiters powers hiring for thousands of enterprises, creating a fragmented but highly structured dataset of global labour demand."
Extracting ATS data across thousands of company portals requires more than simple HTTP requests. We handle the discovery, pagination, JavaScript rendering, and deduplication so your engineering team receives normalised job records ready for analysis.
Everything supported by our smartrecruiters.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, deduplication, and retry logic. Playwright handles JavaScript rendering, cookie sessions, and interaction flows. Combined via scrapy-playwright middleware.
We maintain pools of residential ISP proxies across regions. Rotation happens per-request with sticky sessions where required. IP score monitoring prevents blacklisted pool contamination.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling, dependency management, and SLA alerting. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About smartrecruiters.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available job postings is generally permissible under applicable law. DataFlirt targets only public, non-authenticated job listings and company metadata. We do not extract personal candidate data, circumvent employer authentication walls, or violate GDPR.
Many companies mask their SmartRecruiters ATS behind custom domains. Our pipeline identifies the underlying ATS infrastructure and routes requests through standard extraction logic, ensuring consistent data regardless of the front-end URL.
Yes. Our change detection system maintains a state of all active jobs per portal. When a previously seen job ID is no longer present on the portal, we emit a deletion or closed status record in the next delivery batch.
Pipelines can be configured for daily or hourly runs. Hourly pipelines ensure you receive new job postings within 60 minutes of publication by the employer.
Yes. Employers input locations in various formats. We standardise city, state, and country fields, and explicitly flag remote, hybrid, or on-site designations based on the listing metadata.
Our smallest packages start at a defined list of target company portals with weekly delivery. For large-scale aggregation across thousands of portals, we price based on volume and delivery frequency.
Yes. If the application form is publicly accessible, we can extract the required fields, custom screening questions, and compliance statements associated with the specific job ID.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off export of target companies or a continuous feed of global job postings, we scope, build, and operate the pipeline. Tell us what you need.
