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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
Public LinkedIn job postings become source-linked employer and role records with seniority, location, skills, and posting activity

Schema and fields

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

job_idstring

Source posting identity

titlestring

Displayed role title

companystring

Displayed employer

locationobject

Role geography

employment_typestring

Displayed employment type

descriptionstring

Public posting description

published_attimestamp

Displayed posting time where available

captured_attimestamp

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.

SnapshotStart from a dated baselineSelected scope and collection window
RefreshReceive recurring updatesCadence and change behavior
FormatUse JSON, CSV, or ParquetSchema, partitioning, and manifest
ValidationRun repeatable checksCounts, fields, missing states, and version

LinkedIn applications

Measure hiring demand and skill signals.

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.

  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.

What can I build with LinkedIn data?

  • Hiring-demand analysis

  • Skills intelligence

  • Employer activity research

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.

Start with real records

Request a LinkedIn dataset sample.

Share the sources, fields, markets, and dates you need. Review a sample before choosing delivery.

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