We collect job postings from job boards, aggregators, and company career pages. Exports include titles, salary ranges, requirements and tech stacks, employers, locations, and work arrangements. Posting history shows the labor market in motion and the hiring activity of any company.
Job postings speak openly about the labor market and company plans. Hiring reveals strategy before the press releases do.
Build salary benchmarks on real market ranges: by role, seniority level, and region.
Study the job market: demand for skills, role-based filters, talent shortages, and regional gaps.
Catch the signals: a company hiring for a new initiative is your moment to pitch the product.
Feed your services and models a stream of postings via API, with no collection infrastructure of your own.
Three formats to fit the task: a one-off export, recurring data delivery, or a custom solution. We price each project based on sources, volume, and frequency. Order it once or as a subscription; the quote arrives before the project starts.
Capture postings once: for research, a benchmark, or a data migration.
Data refreshes on a schedule and arrives on its own. New postings are already included.
Turnkey data as a service: API access, DaaS, or a ready-made dashboard, dozens of sources, and an SLA.
How much does job postings scraping cost? The final price is built from a few clear factors, from the number of sources to the depth of processing. We send a quote and a data sample before any work starts.
Describe the roles, companies, and regions, and we'll come back with a cost estimate, timeline, and a data sample within one business day.
A job postings scraper is a tool that turns job ads into structured tables. A robot crawls the listing pages of job boards and company career sections and folds the results into a single schema. Below we break down how the process works and what goes into the export.
Fields for every posting:
Salaries are normalized: pay period, gross or net, currency. Without that, comparing ranges across sites is meaningless. Duplicates of the same posting on different boards are merged into a single record.
Plenty of developers write their own Python script. Then the maintenance work begins: every site has its own markup, boards change it and throttle requests, the code breaks. With our service there's no scraping left for you to do: we take those tasks off your team's plate.
What the process looks like:
Our approach to scraping is polite: pauses between requests, capped request rates, respect for robots.txt and the Retry-After header. The sites aren't disturbed, and the data flow stays stable.
A note on scope: we don't scrape behind logins. We work only with public pages, never inside user accounts. Public community job channels can be added on request; closed social media groups are off limits.
We do not collect resumes or candidate databases. There is no applicant personal data in the export: no contact details, no names. We collect job postings only, meaning the public information companies publish about their hiring.
If you need the companies' own contacts for sales, those are separate services: organization databases are built by company database collection. Outreach is out of scope too: your team sends the emails.
Hiring gives away a company's plans. An "SEO Specialist" opening means a marketing push is coming. Engineers being hired, with a mobile app developer role open, means a product is being built. Every signal shows up in the posting stream, and the volume of information grows with each publication.
Examples of questions this analysis answers:
Alerts for new postings matching your filters arrive by email, in Slack, or straight into your CRM. Monitoring runs on a list of companies or on search parameters. The setup is shaped around your team's needs: you define the selection criteria.
A note on scope: this service covers the labor market. Prices and assortment in online stores are tracked by online store monitoring, and arbitrary websites are handled by web scraping.
Results are delivered in CSV, Excel, JSON, as a feed, or via API. The level of access suits any team: from a spreadsheet for an analyst to a stream into your application. The data slots easily into your existing workflow. To get a sample for your roles, send a request: the sample is free.
Our team has been collecting data from boards and open sources since 2015. Data is valuable when it's clean, complete, and arrives on time.
Ranges are normalized by pay period, tax basis, and currency. Comparisons stay honest.
Requirements are tagged by skill and seniority. Analytics without manual parsing.
One posting on five boards becomes a single record with its source history.
Postings and closings for every company. Hiring dynamics visible month by month.
A transparent process: a quote and a data sample before work starts. No hidden fees or surprises.
You name the roles, industries, companies, and regions.
A data sample and an exact price before work starts.
We connect the sources and configure normalization and filters.
Exports, a feed, or an API, with history and alerts.
Structured job postings: tables ready for benchmarks and analytics.
Titles, salary ranges, requirements, companies, and regions in a single schema.
New and closed postings, salary movement by month and segment.
A stream of postings into your systems and models.
Hiring matched to your filters: companies, roles, regions. An alert the day a posting goes live.
Job postings scraping covers the labor market. We'll set up the adjacent tracks for your task.
Can't find the answer you need? Send a request: support will get back to you within one business day.
Major job boards and aggregators, plus company career pages. If you need a specific site, we'll add it to the list. We work only with public listings, never behind a login.
We collect those too: the share of hidden ranges is a metric in its own right. For benchmarks, a model can estimate the range from similar postings.
By employer, title, and the text of the requirements. One posting across several boards becomes a single record with a list of its sources.
Yes. Monitoring runs on a list of companies: all their postings and hiring dynamics, with alerts for new publications in Slack, by email, or in your CRM.
Projects start at $150. The final price depends on the number of sources, data volume, update frequency, and extra processing (see the factor breakdown above). We send an exact quote and a data sample before work starts and build the database around your roles.
With us, it's a turnkey service. You don't install software or write code: you describe the task, our team sets up the collection and delivers the result. Off-the-shelf scraper tools demand setup and maintenance; here, none of that work is yours.
No. We do not collect resumes, candidate databases, or personal data. The export contains job postings only: the public information companies share about their hiring. There are no applicant contact details in it.
No, we don't scrape behind logins. We collect public listing pages and career sections. Collection stays polite: pauses between requests, capped request rates, and respect for site rules, including the Retry-After header.
A Python script solves the problem once; then the maintenance begins: markup changes, rate limits, errors. We watch every site ourselves and keep the collection tooling in working order, so your project gets data without tying up engineers.