JOB & RECRUITMENT DATA SCRAPING

Hiring signals,
the whole market.

// THE SHORT ANSWER

Job and recruitment data scraping extracts hiring data across the labour market — job postings, roles, required skills, locations, salary bands and posting velocity — from job boards and company career pages. iWeb Data Scraping delivers it QA-verified as CSV, JSON or API, so HR-tech products, staffing firms and investors can track hiring demand, benchmark salaries and read company-growth signals without building collection. Postings are public; applicant personal data is never collected.

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99%+field accuracy, QA-verified
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ISO 27001+ 9001 certified

Key facts

  • Data point: Role title
  • Data point: Company
  • Data point: Normalized role category
  • Data point: Required skills

The job market is one of the richest public data sources there is — a live read on which companies are growing, which skills are in demand, and what roles pay. But it's scattered across dozens of boards and thousands of career pages, each structured differently. Turning it into a usable feed is exactly what recruitment data scraping does.

We capture postings, roles, skills, locations, salary bands and posting velocity across boards and career sites, feeding HR-tech products, staffing intelligence and — via alternative data — investment signals. Related: our Job Postings Data service (ticker-mapped feeds) and Job Postings dataset (ready-to-license).

On compliance: we collect only public job postings — the roles companies advertise — never personal data about applicants. See Trust & Compliance.

THE POINT

One vertical, every platform that matters in it — matched into a single feed your team actually uses.

DATA POINTS WE EXTRACT

Roles, skills, salaries, velocity.

Role title
Company
Normalized role category
Required skills
Location
Salary band (if listed)
Seniority
Posting date
Remote / on-site
Department
Source board
Posting velocity
SEE THE DATA FIRST

What you'll actually receive.

Real sample structure from this feed. Your free 48-hour sample comes in your category, in this shape — CSV, JSON or straight to your warehouse.

Recruitment feed — role, company, location, salary, source.
first_seen company role location salary_band source seniority
2026-07-10 ExampleTech Backend Engineer Bengaluru 18-28 LPA LinkedIn Jobs mid
2026-07-11 RetailCo Store Manager Mumbai 6-9 LPA Naukri mid
2026-07-09 FinServe Data Scientist Remote 25-40 LPA Indeed senior
2026-07-12 HealthPlus Staff Nurse Delhi 3-5 LPA company site junior
↑ Sample structure — illustrative values. Your data reflects your platforms and category. Get this for your data →
WHO USES THIS

Built for the person
who owns the number.

HR-TECH / STAFFING

Power your product

Structured, normalized postings behind matching, market-mapping or salary tools.

TALENT / COMP TEAM

Benchmark the market

Competitor hiring, in-demand skills and salary bands by role and location.

INVESTOR / ALT-DATA

Read company growth

Hiring velocity as a leading indicator — see alternative data.

RELATED:Job Postings Data (service) →Job Postings Dataset →Alternative Data →
FAQ

Before the first call.

Role titles, companies, normalized role categories, required skills, locations, salary bands where listed, seniority, posting dates, remote/on-site, department, source board and posting velocity — from job boards and company career pages, timestamped so trends are trackable.

No — we collect only public job postings, meaning the roles companies advertise. We never scrape or sell personal data about applicants or candidates. This keeps the data on the compliant, public side.

Hiring velocity is a leading indicator: accelerating postings — especially in revenue-generating functions — often precede reported company growth. Investors and analysts use it (ticker-mapped via our Job Postings Data service) as an early signal on companies they cover.

Yes — the same role is titled differently across boards, so we normalize titles into role categories and extract structured skills, making postings comparable across sources rather than leaving you to reconcile inconsistent free text.

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