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Data Marketplace · Jobs & talent

LinkedIn Jobs Dataset

Turn public LinkedIn job postings into structured employer, role, seniority, location, skills, and posting-activity records.

Request LinkedIn sampleView fields
  • Records Job posting · Employer · Role
  • Source LinkedIn
  • Formats JSON · CSV · Parquet
Dataset preview · linkedin jobsReady
Observation 01

An illustrative view of how job posting, employer, role a…

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Field 01
An illustrative view of how job posting, employer, role a…
{
  "job_id": "illustrative-job-42",
  "title": "Data Engineer",
  "company": "Example Systems",
  "location": {
    "country": "DE",
    "city": "Berlin"
  },
  "employment_type": "Full-time",
  "captured_at": "2026-08-07T07:45:00Z"
}
An illustrative view of how job posting, employer, role and collection context arrive together.

Schema and fields

Structure every posting around the role, employer, and location.

Start with job posting, employer, role. Source identity, collection time, and field meaning stay connected so records can move into analysis without losing their context.

job_id string

Source posting identity

title string

Displayed role title

company string

Displayed employer

location object

Role geography

employment_type string

Displayed employment type

description string

Public posting description

published_at timestamp

Displayed posting time where available

captured_at timestamp

Collection time

Freshness and delivery

Track hiring demand as postings appear, change, and close.

Choose recurring delivery when newly observed, changed, and no-longer-observed postings matter to the analysis.

Snapshot Start from a dated baseline Selected scope and collection window

Refresh Receive recurring updates Cadence and change behavior

Format Use JSON, CSV, or Parquet Schema, partitioning, and manifest

Validation Run repeatable checks Counts, fields, missing states, and version

LinkedIn applications

Measure hiring demand and skill signals.

Use source-linked, time-stamped records for hiring-demand analysis, plus skills intelligence. Each application starts from the same documented fields and collection context.

01

Hiring-demand analysis

Compare public role demand across companies, functions, seniority levels, and markets.

02

Skills intelligence

Map skills and requirements from public descriptions into a controlled role taxonomy.

03

Employer activity research

Track posting activity and role mix across selected employers, functions, and markets.

From sample to production

Test LinkedIn Jobs records in your data stack.

Start with representative rows, run the joins and calculations that matter, and shape delivery around the system that will consume the data.

  1. 01

    Choose the useful scope

    Select the entities, markets, fields, dates, and business output the collection should support.

  2. 02

    Run a sample through your stack

    Check identifiers, fields, joins, missing states, and source context with your own queries or models.

  3. 03

    Set the delivery pattern

    Choose the snapshot or recurring schedule, file format, partitions, manifest, and destination.

LinkedIn dataset FAQ

Plan the right LinkedIn Jobs collection.

What does the LinkedIn Jobs Dataset include?

Turn public LinkedIn job postings into structured employer, role, seniority, location, skills, and posting-activity records. Core records include job posting, employer, role, location, skill.

What can I build with LinkedIn data?

Common applications include hiring-demand analysis, skills intelligence, employer activity research. Start with the fields and time window required by the business output.

How can the LinkedIn dataset stay current?

Choose recurring delivery when newly observed, changed, and no-longer-observed postings matter to the analysis.

When should I use the LinkedIn API instead?

Use the on-demand API when your application chooses individual requests and timing. Choose this dataset for a prepared bulk snapshot or recurring file delivery.

Continue the data journey

Connect LinkedIn data to the wider use case.

Compare the adjacent dataset, open the source API, or continue into the relevant data, industry, and solution pages.

Start with real records

Request a LinkedIn dataset sample.

Tell us which job posting and employer data you need, plus the markets, fields, dates, and destination. We will map the collection to that requirement.

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