Apify Indeed Scraper: Job Listings at Scale (2026)

What the scraper pulls

Per listing: job title, company, location (city/remote), salary range where posted, posting date, job type, and the full description text. Input is a search query + location, a company name, or a list of job URLs.

The salary field is the differentiator: Indeed displays pay on a far larger share of listings than LinkedIn — scraped at scale, it is a benchmarking dataset.

Setup: first pull in minutes

1. Apify Store → Indeed scraper — input keyword + location ("marketing manager" + "remote")
2. Options max results, country site, posted-within filters
3. Test run on 100 listings — inspect the fields, salary coverage in your niche — Test run on 100 listings — inspect the fields, salary coverage in your niche
4. Export CSV/JSON — full descriptions included for skill-mining — Export CSV/JSON — full descriptions included for skill-mining
5. Scale multiple role families, weekly schedules

For recruiters: market and sourcing intel

Before writing a JD, scrape the role: what competitors title it, what they pay (posted salaries), which skills dominate the descriptions, and how many are hiring at once. A scrape of 200 listings answers "is our offer competitive" better than any survey.

Company-level scraping flips it: all open roles at a target employer shows their growth direction — a competitor posting 15 data engineers is telling you their roadmap. The recruitment playbook builds the full system.

Salary benchmarking at scale

Scrape the same role across geographies and the posted-salary distribution becomes your comp benchmark: median, range, remote-vs-onsite delta — real posted data, not self-reported estimates.

For job seekers: the same scrape shows who is actually hiring, what the real titles are, and which skills the postings keep demanding — a job-search strategy built on data.

Labor-market signals

Weekly scrapes on a keyword set = a homemade labor-market index: posting volume by role family, hiring velocity by company, emerging skill demands appearing in descriptions before they trend.

For B2B sales: companies hiring aggressively in a function are buying signals — a firm posting 10 sales roles needs tooling before the quarter ends. Route new postings to outreach via lead pipelines.

Cadence and limits

Indeed is a defended site — the actors handle the anti-bot, but keep runs targeted: your role families weekly, specific companies monthly. Whole-site harvests are where blocks and costs climb.

Public job data for analysis is standard practice — the frame in web scraping legality applies. Cost is trivial: hundreds of listings per run, cents per thousand.