Hiring demand and pay, read from live job postings.
Job postings are one of the clearest public signals of where companies are investing. We collect postings from job boards and company career pages, normalise titles, skills and salaries, and remove reposts, so you can analyse hiring demand and pay by role and market.
Job data is noisy: the same role is posted on many boards, titles vary widely, and salaries are quoted monthly, yearly, gross or net, in different currencies. Raw counts and averages mislead without careful cleaning.
You get a de-duplicated postings dataset with standardised titles, skills and annualised salary ranges. HR, strategy and investment teams can compare demand and pay across companies, cities and time.
Everything needed to run it in production.
Board and career page coverage
Postings from job boards, recruitment agency sites and employer career pages across your target markets.
Repost de-duplication
The same vacancy posted on several boards or reposted over time is merged into one record.
Title normalisation
Job titles are mapped to a standard occupation taxonomy and seniority level.
Skills extraction
Skills, tools, certifications and languages are extracted from posting text.
Salary normalisation
Advertised pay is converted to annual gross ranges in local currency, with the original wording retained.
Employer mapping
Postings are linked to employer entities, including recruiters posting on behalf of clients where identifiable.
What lands in your systems.
| posted_date | city | normalised_title | seniority | salary_min_annual | salary_max_annual | currency | remote |
|---|---|---|---|---|---|---|---|
| 2026-08-12 | Dubai | Data engineer | Mid | 216,000 | 288,000 | AED | hybrid |
| 2026-08-12 | Riyadh | Supply chain manager | Senior | 300,000 | 396,000 | SAR | onsite |
| 2026-08-13 | Jakarta | Digital marketing specialist | Junior | 96,000,000 | 132,000,000 | IDR | hybrid |
| 2026-08-14 | Toronto | Product analyst | Mid | 85,000 | 105,000 | CAD | remote |
| 2026-08-14 | Amsterdam | Warehouse team lead | Mid | 42,000 | 50,000 | EUR | onsite |
Illustrative rows. Your schema, field names and formats are agreed during scoping.
Who uses it, and for what.
Analysts track hiring volumes by company and function as a leading indicator of expansion. A slowdown in postings can signal a change in strategy.
HR and reward teams benchmark advertised salaries for key roles by city. Pay ranges are reviewed against the live market rather than annual surveys alone.
Recruitment and HR technology firms find companies that are hiring heavily in their target roles. Outreach is directed to employers with active demand.
Labour market analysts model skills demand and wage trends across regions. Normalised titles make comparisons across boards and countries possible.
- Scope. Tell us the sources, fields and frequency. We confirm feasibility within a day.
- Free sample. A real sample from your own target source, in your format.
- Build. Engineers build extractors tuned to each source. No generic templates.
- Validate. Automated and manual QA on every run before anything ships.
- Deliver and monitor. Scheduled delivery, monitored pipelines, fast fixes when sites change.
Related services
Industries that use it
How do you handle salaries quoted in different ways?
We parse the advertised figure and its period, then convert to an annual gross range in local currency. The original text is kept so any assumption can be checked.
What share of postings include salary?
It varies widely by market, board and role. We report the salary fill rate in each delivery so you know how representative the salary figures are.
Do you collect candidate data?
No. We collect job postings published by employers and recruiters, not information about job seekers or CVs.
How are duplicate postings removed?
We match postings on employer, title, location and text similarity across boards and over time. Reposts are merged so each vacancy is counted once, with its first and last seen dates.