We extract tech job listings, skill requirements, experience brackets, company profiles, and recruiter data from Hirist. 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 hirist.com. All fields typed and schema-versioned.
"job_id": "H-89210", "title": "Senior Backend Engineer", "company_name": "FintechCorp", "location": "Bengaluru", "experience_min": 4, "experience_max": 8, "skills": "['Python', 'Django', 'PostgreSQL']", "posted_date": "2026-05-10"
| # | job_id | title | company_name | location | experience_min | experience_max |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Company Profiles objects from hirist.com. All fields typed and schema-versioned.
"company_id": "C-4421", "name": "FintechCorp", "industry": "Financial Services", "website": "https://fintechcorp.example.com", "funding_stage": "Series B", "employee_count": "201-500", "active_jobs": 14
| # | company_id | name | industry | website | funding_stage | employee_count |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Skill & Tech Stack objects from hirist.com. All fields typed and schema-versioned.
"job_id": "H-89210", "primary_skills": "['Python', 'AWS']", "frameworks": "['Django', 'FastAPI']", "languages": "['Python', 'Go']", "databases": "['PostgreSQL', 'Redis']", "cloud_providers": "['AWS']"
| # | job_id | primary_skills | secondary_skills | frameworks | languages | databases |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Recruiter Data objects from hirist.com. All fields typed and schema-versioned.
"recruiter_id": "R-9921", "name": "Priya Sharma", "title": "Talent Acquisition Lead", "company": "FintechCorp", "active_postings": 8, "joined_date": "2023-11-04"
| # | recruiter_id | name | title | company | active_postings | total_hires |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Search Results objects from hirist.com. All fields typed and schema-versioned.
"keyword": "Data Engineer", "location_filter": "Remote", "position": 3, "job_id": "H-90112", "title": "Data Engineer II", "company_name": "DataFlirt", "is_promoted": false, "scraped_at": "2026-05-12T10:14:33Z"
| # | keyword | location_filter | experience_filter | position | job_id | title |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Hirist scraper navigates complex client-side rendering and infinite scroll mechanics to extract structured job postings, skill requirements, and company intelligence.
Title, description, experience brackets, locations, and metadata extracted at the job-ID level.
Extract structured arrays of required technologies, languages, and frameworks from raw job descriptions.
Capture funding stage, employee count, and active job volume for hiring companies.
Extract hiring manager details and active posting counts to map talent acquisition teams.
Track which companies are paying to boost their listings in search results.
Capture disclosed salary ranges and equity components when available in the listing.
Identify hybrid, remote, and onsite mandates accurately from location tags and descriptions.
Only ingest new jobs and closed positions since the last run to optimise warehouse compute.
Scrape jobs across Bengaluru, NCR, Mumbai, and remote filters concurrently.
Brief in. Clean data out.
Provide target roles, locations, or companies. We map the extraction schema.
We configure Scrapy crawlers, handle Hirist SPA pagination, and set up proxy rotation.
Schema validation, missing field checks, and sample data review before launch.
JSON, CSV, or Parquet pushed to your S3 bucket or data warehouse on schedule.
Hirist relies heavily on client-side rendering and infinite scroll. We manage the browser execution layer so you get clean structured data.
Hirist uses React. We run Playwright to hydrate the DOM and trigger API payloads, capturing data that simple HTTP requests miss.
We simulate human scroll behaviour to load all listings in a category without triggering rate limits or missing intermediate elements.
We route requests through Indian residential IPs to avoid geo-blocking and CAPTCHA walls, maintaining high success rates.
We map unstructured job descriptions into clean JSON arrays for skills, frameworks, and experience brackets.
We track job IDs over time to flag when a position is closed or removed, keeping your dataset accurate.
Track hiring volume by city, tech stack, and company size to understand market trends.
Monitor which roles your competitors are hiring for and their required skill sets.
Identify companies actively hiring specific tech roles to pitch recruitment services.
Aggregate compensation data across roles and experience levels to optimise your own offers.
Analyse the most demanded frameworks and languages to design relevant training courses.
Track startup hiring velocity as a proxy for recent funding or growth trajectory.
"Hirist holds the most concentrated dataset of Indian tech hiring signals, but extracting it requires navigating heavy client-side rendering and infinite scroll mechanics."
Building a reliable Hirist scraper means managing headless browsers, residential proxy pools, and complex DOM hydration. DataFlirt handles the infrastructure layer, delivering clean job postings and company profiles directly to your warehouse. Your team focuses on talent analytics, not bot evasion.
Everything supported by our hirist.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.
Playwright instances running on Kubernetes to handle Hirist client-side rendering and DOM hydration.
Localized Indian IP addresses to prevent rate limiting and CAPTCHA interventions during high-volume extraction.
PostgreSQL-backed state management to emit only new or closed jobs, reducing downstream processing loads.
Data delivered to where your team already works — no new tooling required.
About hirist.com scraping, legality, and pipeline operations.
Ask us directly →Scraping public job postings is generally permissible. DataFlirt extracts only public job listings, company profiles, and recruiter data. We do not extract private candidate resumes or bypass authentication walls.
We use Playwright to simulate user scroll events, ensuring all XHR requests fire and the DOM fully populates before extraction.
Yes, when explicitly stated in the job description or metadata, we parse it into structured minimum and maximum integer fields.
We maintain state across pipeline runs and flag jobs that no longer appear in search results or return 404 status codes.
No, we only extract public job postings and company data. We do not scrape gated candidate resumes or personal contact information.
We typically run daily pipelines, but can configure hourly syncs for high-priority keywords or specific company profiles.
20-minute scoping call. Pilot dataset within the week. Production within two. Scope your target roles, locations, or companies. We build the infrastructure and deliver structured data to your warehouse.
