Latenode
LinkedIn
Headless browser
Google sheets

Automate LinkedIn job data scraping and analysis in Google Sheets

This workflow allows users to automatically scrape recent job listings from LinkedIn using Bright Data's Dataset API. The extracted data is then cleaned and added to a Google Sheet, providing valuable insights for both job seekers and sales/prospecting teams.

Users can filter the search by location, keyword, job type, experience level, and remote work options. The workflow includes robust error handling and retry logic to ensure reliable data collection. By leveraging this automation, users can quickly identify hiring signals, spot relevant job openings, and prioritize outreach to companies actively growing in their target market.

Updated Apr 2, 2026Est. run: 9sEst. cost: $0.0006
How Latenode estimates time and cost

Latenode bills workflow runs in credits: 1 credit = 30 seconds of processing. Minimum charge per run depends on your plan. Plug-and-Play (PnP) AI nodes are billed separately—each PnP token is $1 USD, charged pay-as-you-go at vendor cost plus a small processing fee, with no API keys required.

Full pricing — how credits work →
Scraping & data collection

Workflow preview

What this template does

  • Extracts recent job listings from LinkedIn
  • Normalizes and cleans the extracted data
  • Stores the job data in a Google Sheet
  • Allows filtering by location, keyword, job type, experience, and remote work
  • Generates a Google Sheet with actionable hiring insights

How it works

1
Trigger

Configure Job Search Criteria

Users start by specifying the location, keyword, job type, experience level, and remote work options they want to search for on LinkedIn.

2
Action

Scrape LinkedIn Job Listings

The workflow uses the Bright Data Dataset API to automatically fetch the most recent job postings that match the user's search criteria from LinkedIn.

3
Logic

Clean and Normalize Job Data

The raw job listing data is then cleaned, with fields flattened and HTML removed from the job descriptions to prepare the information for analysis.

4
Action

Log Job Data to Google Sheets

The cleaned and normalized job data is saved to a pre-configured Google Sheets spreadsheet, providing a centralized hub for further analysis and insights.

Setup guide

1

Connect Bright Data Credential

Add your Bright Data API key credential in the Latenode Credentials panel. This will allow the workflow to authenticate with the Bright Data Dataset API.

2

Configure Google Sheets Connection

Set up your Google Sheets OAuth2 credential in the Latenode Credentials panel. This will grant the workflow access to write data to your Google Sheets.

3

Customize Search Filters

In the Latenode Form node, configure the location, keyword, and country code fields that users will use to search for LinkedIn job listings. You can also enable optional filters like job type, experience level, and remote work.

4

Manage Headless Browser Session

In the Latenode Headless Browser node, set up the browser session and handling of cookies/login. This ensures the workflow can access LinkedIn and retrieve job listings.

5

Review and Customize Output

Inspect the data schema in the Latenode JavaScript node, where the job listing data is cleaned and prepared for the Google Sheets integration. Customize the field mapping and formatting as needed.

Requirements

LinkedIn account with permission to access the dataset API
Google Sheets account with a spreadsheet to store the extracted job data
Access to the Latenode workspace to configure the headless browser and code nodes
Knowledge of basic web scraping concepts and techniques

FAQ

Common questions about this template

Each run uses credits on your Latenode plan. We charge for processing time (1 credit = 30 seconds). Your actual cost depends on your plan and how long the run takes. See pricing plans for plans and how credits work.
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