Skip to content
Canaria

Provider Comparison / Where to buy

Where to Buy Job Postings Data: 2026 Buyer's Guide

Short answer: you can buy job postings data in four ways: directly from a provider, through a data marketplace, by scraping it yourself, or from free public sources. Buying direct gives you the most control over fields, history and price; marketplaces make discovery and procurement easier; scraping and public sources trade money for engineering time or coverage.

Canaria publishes this guide and sells job postings data, so we say where we fit and where we do not.

By the Canaria data team · Last verified September 15, 2026

1. Buy directly from a job data provider

Providers fall into three groups, and the right one depends on how much cleaning you want done before the data arrives.

  • Enriched job data at self-serve prices: Canaria. Postings arrive deduplicated to one record per job, with occupation and industry codes, normalized titles, skills, salary estimates and per-field confidence scores, from a free tier and $49 a month.
  • Enterprise labor market platforms: Lightcast, Revelio Labs and LinkUp. Deep history and global breadth, sold under annual contracts that are typically six figures.
  • Raw and self-serve feeds: Coresignal, TheirStack, PredictLeads. Lower entry prices, with more of the classification left to the buyer.

Our ranked list of 13 providers compares them by use case, coverage and price.

2. Buy through a data marketplace

Data marketplaces list datasets from many vendors and often let you buy through an account your company already has.

MarketplaceWhat it isJob data providers listed
DataradeDirectory and marketplace for commercial datasetsCanaria is listed second on its job postings category, alongside Coresignal, Xverum and PredictLeads. Canaria on Datarade
Databricks MarketplaceData products delivered into DatabricksCanaria. Canaria on Databricks
Snowflake MarketplaceDatasets shared directly into SnowflakeLightcast, Revelio Labs and LinkUp list there; Canaria delivers by Snowflake share
AWS MarketplaceDatasets and APIs billed through AWSLightcast lists there
Nasdaq Data LinkAlternative data for investorsLinkUp lists there

Competitor listings as stated in each provider's own documentation.

3. Scrape job postings yourself

Scraping platforms such as Bright Data and Oxylabs sell proxies, scraper APIs and ready-made datasets for job boards. This is the cheapest route per raw record and the most expensive in engineering time.

  • Sources change their pages, so scrapers need constant upkeep.
  • The same job appears on several boards and must be deduplicated.
  • Occupations, industries, titles and skills still need classifying.
  • Each site's terms of use need a legal review.

We estimate the full in-house build at $500,000 to $1 million in the first year. The pricing guide compares that with buying.

4. Free and public sources

Useful for narrow questions, not as a full postings feed:

  • USAJOBS API: postings for US federal government jobs.
  • BLS JOLTS: monthly US job-openings estimates from an employer survey. It counts openings, not postings, and has no employer-level detail.
  • State labor market information offices: regional employment and wage statistics.
  • Free vendor tiers:Canaria's free API tier (500 credits a month) and free 5,000-record sample.

What to check before you buy

  1. Unique versus collected counts. One job posted to five boards should count once. Canaria collects 1B+ postings and ships 400M+ unique jobs after semantic deduplication.
  2. Field coverage. Ask what share of records has each field you need populated, not just whether the field exists.
  3. Point-in-time history. Backtests need data collected when it happened, with first-seen and last-seen dates.
  4. Stable identifiers. If job IDs change between deliveries, your joins and saved records break.
  5. License and delivery. Confirm usage rights, formats (CSV, Parquet, JSON) and destinations (S3, GCS, Snowflake, SFTP) in writing.

The Canaria schema lists every field we deliver.

Frequently Asked Questions

Where can I buy job postings data?
Four places: directly from a job data provider (for example Canaria, Lightcast, Revelio Labs, LinkUp, Coresignal or TheirStack), through a data marketplace such as Datarade, Databricks Marketplace, Snowflake Marketplace or AWS Marketplace, by scraping job sites with a platform such as Bright Data or Oxylabs, or from free public sources such as the USAJOBS API for federal jobs. Buying direct usually gets the best price and the most control over fields and delivery.
Is it better to buy job data from a marketplace or directly?
Marketplaces are good for discovery and for procurement through an account you already have. Buying directly is better for custom filters, historical backfills, usage rights and price, because the marketplace listing is usually a standard package. Many buyers find a provider on a marketplace and then contract directly.
Can I scrape job postings myself instead of buying them?
You can, with scraping platforms that handle proxies and page rendering. The cost is rarely the scraping itself: it is keeping hundreds of sources working, removing duplicates across sites, classifying occupations and industries, and reviewing each site's terms of use. Canaria estimates the full in-house build at $500,000 to $1 million in the first year.
What should I check before buying job postings data?
Test a sample built on your own filters, and check five things: the ratio of unique jobs to collected postings, the share of records where each field you need is populated, whether history was collected at the time (first-seen and last-seen dates), whether job IDs stay stable across deliveries, and what the license lets you do with the data.

Test Canaria against your shortlist

Get 5,000 enriched records tailored to your criteria, free.

Prefer to talk it through?

Schedule a 30-min demo
Canaria is not affiliated with, endorsed by, or connected to any other company named on this page. Competitor information comes from each provider's public documentation and pricing pages. Where we say a provider's documentation does not describe something, we did not find it there; the provider may still offer it. Last verified: September 15, 2026. Contact us if you find an error.