We extract job postings, company directories, salary ranges, and skill taxonomies from Foundit. 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 foundit.in. All fields typed and schema-versioned.
"job_id": "8491023", "title": "Senior Python Developer", "company_name": "TechCorp India", "location": "Bengaluru", "experience_req": "5-8 Years", "salary_range": "Not Disclosed", "posted_date": "2026-05-10T08:30:00Z", "apply_url": "https://www.foundit.in/job/senior-python-developer-8491023"
| # | job_id | title | company_name | location | experience_req | salary_range |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Company Profiles objects from foundit.in. All fields typed and schema-versioned.
"company_id": "C9281", "name": "TechCorp India", "industry": "IT Software / Software Services", "employee_count": "1001-5000", "headquarters": "Bengaluru", "active_jobs_count": 42, "rating": 4.1, "website": "https://techcorp.in"
| # | company_id | name | industry | employee_count | headquarters | about |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Skills & Taxonomies objects from foundit.in. All fields typed and schema-versioned.
"job_id": "8491023", "primary_skills": "['Python', 'Django', 'PostgreSQL']", "secondary_skills": "['Docker', 'AWS', 'Redis']", "education_req": "B.Tech/B.E. in Computers", "function_area": "IT Software - Application Programming", "role_category": "Programming & Design", "employment_type": "Full Time, Permanent", "notice_period": "30 Days"
| # | job_id | primary_skills | secondary_skills | certifications | education_req | industry_tags |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Salary Data objects from foundit.in. All fields typed and schema-versioned.
"job_id": "8491023", "min_salary": 1500000, "max_salary": 2500000, "currency": "INR", "is_disclosed": true, "salary_type": "Annual", "experience_tier": "Mid-Senior", "bonus_included": false
| # | job_id | min_salary | max_salary | currency | is_disclosed | salary_type |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Search Results objects from foundit.in. All fields typed and schema-versioned.
"keyword": "Data Engineer", "location": "Pune", "position": 3, "job_id": "9182734", "title": "Data Engineer II", "company": "DataFlirt", "is_promoted": false, "scraped_at": "2026-05-12T09:14:33Z"
| # | keyword | location | position | job_id | title | company |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Foundit scraper handles every layer of the platform: job listings, company directories, skill taxonomies, and salary data. JavaScript rendering and anti-bot circumvention built in.
Title, description, location, experience requirements, and every metadata field Foundit surfaces, scraped at the individual job level.
Capture company name, industry, employee count, active job listings, and corporate descriptions across the platform.
Extract primary skills, secondary skills, and educational requirements as structured arrays for easy database ingestion.
Capture minimum and maximum salary bands, currency, and disclosure flags for accurate compensation benchmarking.
Identify on-site, hybrid, and fully remote roles, alongside multi-city location mapping for nationwide postings.
Monitor walk-in drive schedules, venue details, and specific dates for volume hiring campaigns.
Distinguish organic job search results from sponsored or promoted placements to map competitor ad spend.
Run one-off bulk exports or configure continuous pipelines at daily cadences with change-detection diffing.
Target foundit.in, foundit.my, foundit.sg, and other regional variants from a unified extraction schema.
Brief in. Clean data out.
Provide search keywords, location sets, or company IDs. We design the extraction schema together.
We configure Scrapy crawlers, proxy rotation, session management, and pagination handling for foundit.in.
Schema validation, null-rate checks, and sample job records before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Job boards invest heavily in rate limiting and bot detection. Here is how we stay resilient.
Foundit uses advanced rate limiting and IP reputation checks. Our crawlers use residential ISP proxies with realistic browser fingerprints and randomised request timing.
Job search results rely on infinite scroll and complex API pagination. We reverse-engineer the underlying XHR requests to extract records without dropping pages.
Foundit updates its DOM structure frequently. Our selector strategy uses multiple fallback chains per field, so a layout change does not break your data pipeline.
For large job catalogues, we maintain a hash index of last-seen values per field. Subsequent runs only push diffs, reducing compute cost and downstream processing load.
Every run emits structured logs to our observability stack. We alert on null-rate spikes and coverage drops, responding before you notice.
Niche job boards and aggregators sync Foundit listings to backfill their own search indexes and provide comprehensive market coverage.
Economic research firms track hiring volume, skill demand shifts, and location-based job growth over time.
HR tech platforms aggregate disclosed salary ranges to build compensation models and benchmark industry standards.
Sales teams monitor companies actively hiring specific roles to trigger targeted outreach for software and services.
Corporate strategy teams track competitor job postings to infer product roadmaps, expansion plans, and technology stack shifts.
EdTech companies analyse primary and secondary skill requirements to design relevant courses and certification programs.
"Foundit holds critical signals on India's hiring market, skill demand, and salary benchmarks, but extracting it requires dedicated infrastructure."
Most teams underestimate the investment required: reliable Foundit scraping requires residential proxies, pagination handling, and daily selector maintenance. DataFlirt absorbs that complexity so your engineers can focus on the analysis, not the infrastructure.
Everything supported by our foundit.in 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 IN 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 foundit.in scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available job postings and company profiles is generally permissible. DataFlirt targets only public, non-authenticated data. We do not extract personal candidate data, resumes, or circumvent authentication walls. Clients should consult legal counsel for specific use cases.
We use residential ISP proxies, realistic browser fingerprints, and request timing modelled on human behaviour. We monitor for 429/CAPTCHA rate spikes in real time and trigger pool rotation automatically.
Yes. We parse the job descriptions and metadata to extract primary skills, secondary skills, and educational requirements into structured arrays.
Pipelines typically run on a daily cadence, ensuring you have the latest job postings and closed-job status updates within 24 hours.
Yes, we extract disclosed minimum and maximum salary bands, currency, and salary types. Non-disclosed salaries are flagged accordingly.
We capture data from the day your pipeline is commissioned. We do not maintain a historical backfill of Foundit data prior to your contract start date.
No. Candidate profiles and resumes are gated behind recruiter logins and contain PII. We strictly extract public job and company data.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a daily feed of IT jobs or a full export of company profiles, we scope, build, and operate the pipeline. Tell us what you need.
