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ScrapeLinkedInLinkedInprofiles by search term
Scrape LinkedIn profiles by search term. Extract Google Maps business listings and reviews. Collect Facebook pages, groups and posts. Scrape Instagram profiles, reels and comments. Extract TikTok posts and creator profiles. Collect YouTube channels and video data. Scrape X / Twitter profiles and posts. Extract Indeed job listings and salaries. Collect Yelp business reviews and ratings.
Home/Integrations/How to Scrape LinkedIn Job Listings into Make
LinkedInMake

How to Scrape LinkedIn Job Listings into Make

Extract job listings data from LinkedIn and pipe into Make automatically

Step-by-step guide

1

Choose the LinkedIn Job Listings scraper

Navigate to the LinkedIn Job Listings scraper in Scrapernode. Select "Fresh Scrape" for real-time data or "Quick Lookup" for pre-collected records. Each record costs 1 credit.

2

Set up your Make connection

Create a new Make scenario with a Webhook trigger module. Copy the webhook URL into Scrapernode's webhook settings. Use Make's built-in JSON parser to map scraper fields to downstream modules like "Create Spreadsheet Row" or "Send Email".

3

Provide your LinkedIn input URLs

Paste the LinkedIn URLs you want to scrape — one per line, or upload a CSV. Scrapernode accepts direct profile links, search result URLs, and content pages.

4

Launch the scraping job

Click "Start Extraction" to begin. Scrapernode handles proxy rotation, rate limiting, and anti-bot detection automatically. Jobs typically complete in under 60 seconds per batch.

5

Receive data in Make

When the job completes, Scrapernode sends the full results to your Make workflow. Each record includes 27 fields like url, job_posting_id, job_title, company_name. Route the data to any downstream app — CRMs, databases, email tools, and more.

Cost per record

1 credit

Output fields

27 fields

Destination

Make

Sample Output

Preview the data you'll receive — 5 sample records

Record 1 of 5
Url
sample_url
Job Posting Id
sample_job_posting_id
Job Title
Senior Product Manager
Company Name
Notion Labs, Inc.
Company Id
sample_company_id
Job Location
San Francisco, CA (Hybrid)
Job Summary
sample_job_summary
Job Seniority Level
Mid-Senior level
Job Function
sample_job_function
Job Employment Type
Full-time
Job Industries
sample_job_industries
Job Base Pay Range
sample_job_base_pay_range
Company Url
sample_company_url
Job Posted Time
sample_job_posted_time
Job Num Applicants
96
Discovery Input
sample_discovery_input
Apply Link
sample_apply_link
Country Code
US
Title Id
sample_title_id
Company Logo
sample_company_logo
Job Posted Date
2025-12-15
Job Poster
sample_job_poster
Application Availability
Yes
Job Description Formatted
sample_job_description_formatted
Base Salary
sample_base_salary
Salary Standards
sample_salary_standards
Is Easy Apply
Yes

Data Dictionary

27 fields returned per record

The job posting's web link on LinkedIn (100.00% fill rate)

Unique identifier for each job listing (100.00% fill rate)

Title of the advertised job position (99.70% fill rate)

Name of the hiring company (99.35% fill rate)

Unique identifier for each company (99.35% fill rate)

Geographic location of the job (99.70% fill rate)

Brief overview of job responsibilities (99.70% fill rate)

Seniority level of the position (99.70% fill rate)

Specific department or function of the job (98.35% fill rate)

Type of employment offered (99.70% fill rate)

Industries associated with the job (99.50% fill rate)

Salary range for the position (13.27% fill rate)

LinkedIn profile link of the hiring company (99.35% fill rate)

Timestamp for when the job was posted (99.70% fill rate)

Number of applicants for the job (100.00% fill rate)

Discovery input values (99.51% fill rate)

Sub-fields

keywordTextSearch keyword
locationTextSearch location
time_rangeTextTime range filter for job search
selective_searchBooleanWhether selective search is enabled
remoteTextRemote work filter
job_typeTextJob type filter
experience_levelTextExperience level filter
countryTextCountry filter for job search

Link or information for job application (18.96% fill rate)

2 letter country code (30.51% fill rate)

Standardized LinkedIn job title ID (96.78% fill rate)

The logo image of the company posted the job (99.35% fill rate)

Parsed date of the job posting time (99.70% fill rate)

Profile of the person who posted the job (99.24% fill rate)

Sub-fields

nameTextJob poster name
titleTextJob poster title
urlTextJob poster profile URL

Whether a user can still apply for this job (99.65% fill rate)

The job description as it appears in LinkedIn (99.70% fill rate)

Structured base pay range with currency and pay period (99.24% fill rate)

Sub-fields

min_amountNumberMinimum salary amount
max_amountNumberMaximum salary amount
currencyTextSalary currency
payment_periodTextSalary payment period (yearly, monthly, etc.)

Employer-provided pay standards or notes (13.27% fill rate)

Does it have easy apply (99.51% fill rate)

Frequently Asked Questions

Common questions about How to Scrape LinkedIn Job Listings into Make

Ready to connect LinkedIn data to Make?

Start extracting linkedin job listings data and pipe into Make in minutes.

Go to LinkedIn Job Listings scraperBrowse all integration guides
No code requiredAuto-delivery to Make27 data fields