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Job posting scraper

Job posting scraper

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Collect job listings from URLs into structured rows. Capture title, company, location, date, and details. Export to CSV or JSON for tracking.

Want to scrape data in bulk? Try Thunderbit for free.

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Scrape Job Listings with AIUse Thunderbit’s Chrome extension to scrape job boards and career pages fast, then extract structured fields with minimal setup. Automate collection across pages and exports.
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Scrape Job Listings with AI

Thunderbit scrapes job boards, company career pages, and listing directories, then extracts structured fields like role, company, location, posting date, and description. Use AI Suggest Fields to set columns in seconds, handle pagination, and enrich results by scraping subpages for full job details. Scrape from websites and also pull data from subpages, PDFs, docs, images, and screenshots when listings are embedded in files. Summarize, categorize, and format the output, then export to Google Sheets, Airtable, or Notion for tracking pipelines and reporting.

How to Scrape Job Postings Using Thunderbit

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STEP 1Download and InstallDownload and install the Thunderbit Chrome Extension from the Thunderbit Chrome Extension Download Page. Once installed, log in or create a free account to get started.
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STEP 2Open ExtensionOpen Chrome and go to the job board or careers page you want to scrape. Click the Thunderbit extension icon to open Thunderbit, then select the Job Posting Scraper. In the tool, choose either the "Enter Job Listing Page URL(s)" tab to paste multiple URLs (one per line) or the "Enter a Single Job Listing Page URL" tab for one URL. Optionally add filters such as job title keywords (comma-separated), a company name filter, and a location filter to narrow the results before running the scraper.
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STEP 3Click the Scrape job postings ButtonClick the "Scrape Job Postings" button to start extraction. Thunderbit will parse the provided page URL or URLs and return a structured table with fields such as Job Title, Company, Location and Posting Date. Review the table in Thunderbit, then export the results as CSV or JSON for analysis or tracking.

Learn how to scrape job postings from job boards and career pages

Collect job listings from multiple URLs

Job Posting Scraper pulls structured job data from one or many job listing pages you provide. Paste URLs from job boards or company career pages, then scrape a table that includes Job Title, Company, Location, Posting Date, Job URL, and Job Details. It’s built for recruiters, job seekers, and operations teams who need a reliable way to turn scattered listings into a searchable dataset.
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Filter results by title, company, and location

Refine what you collect using optional filters such as job title keywords, a company name match, and a location filter like a city or “Remote.” This helps teams focus on relevant roles without sorting through unrelated postings. It’s useful for staffing agencies tracking specific roles, hiring managers monitoring competitors’ openings, and analysts building targeted labor market snapshots.
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Track hiring trends and build role pipelines

Use the output table to monitor hiring activity over time, compare locations, and spot new openings as they appear. For recruiting teams, the scraper supports building a pipeline by consolidating roles across multiple sources into one view. For job seekers, it helps maintain a personal tracker of roles, links, and details so follow-ups and applications stay organized.
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Export structured data for reporting and workflows

After scraping, export job postings as CSV or JSON for analysis, sharing, or importing into your existing tools. The structured fields make it easier to deduplicate listings, sort by posting date, and create weekly reports. Teams can also use the Job URL field to revisit postings, while Job Details supports downstream steps like categorization, summaries, or internal notes.
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What users say about Thunderbit

Taryn W.Growth Strategist@Thunderbit changed how I run competitor research. I click 'AI Suggest Fields,' and it builds a clean table across paginated results—no coding, no CSS. Huge time-saver when analyzing product data from long-tail marketplaces.
Miles T.Sales Development ConsultantI use Thunderbit to grab emails and phone numbers from directories. It extracts clean contact info in one click, and exporting to Sheets or Notion takes seconds. No extra setup, no coding—just usable data ready to work with.
Rhea C.E-commerce AnalystThunderbit helps me monitor SKU data across multiple pages. I scrape the listings, then use Subpage Scraping to pull full product specs, pricing, reviews, and stock. The AI organizes everything into columns I define.
Cassian B.Real Estate AdvisorThunderbit's Scheduled Scraper makes real estate tracking easier. I describe the interval in plain English, and it automatically pulls updated listings, prices, and links without touching the setup again. Simple and very practical.
Dorian B.Content & SEO SpecialistI use Thunderbit's Field AI Prompts to clean and tag scraped blog content. It extracts titles, authors, and even suggests categories. Works great across dynamic sites and subpages—perfect for building structured SEO datasets.
Lina K.Marketplace Operations LeadWe track SKUs from niche stores using Thunderbit. Cloud Scraping handles 50 pages at a time, and for login-required sites, we switch to browser mode. It’s fast, flexible, and doesn’t need ongoing maintenance or manual edits.
Jorge F.Inbound Sales ManagerThunderbit’s AI Autofill is a lifesaver. After scraping contact info, I use it to fill lead forms directly in my browser. I just select the tab, and it fills everything using the scraped row. No manual input needed.
Alina D.Freelance ResearcherI rely on Thunderbit for extracting data from PDFs, image-based sites, and infinite scroll pages. It handles messy formats with AI and delivers ready-to-export tables I can send to Google Sheets or Airtable in seconds.
Taryn W.Growth Strategist@Thunderbit changed how I run competitor research. I click 'AI Suggest Fields,' and it builds a clean table across paginated results—no coding, no CSS. Huge time-saver when analyzing product data from long-tail marketplaces.
Miles T.Sales Development ConsultantI use Thunderbit to grab emails and phone numbers from directories. It extracts clean contact info in one click, and exporting to Sheets or Notion takes seconds. No extra setup, no coding—just usable data ready to work with.
Rhea C.E-commerce AnalystThunderbit helps me monitor SKU data across multiple pages. I scrape the listings, then use Subpage Scraping to pull full product specs, pricing, reviews, and stock. The AI organizes everything into columns I define.
Cassian B.Real Estate AdvisorThunderbit's Scheduled Scraper makes real estate tracking easier. I describe the interval in plain English, and it automatically pulls updated listings, prices, and links without touching the setup again. Simple and very practical.
Dorian B.Content & SEO SpecialistI use Thunderbit's Field AI Prompts to clean and tag scraped blog content. It extracts titles, authors, and even suggests categories. Works great across dynamic sites and subpages—perfect for building structured SEO datasets.
Lina K.Marketplace Operations LeadWe track SKUs from niche stores using Thunderbit. Cloud Scraping handles 50 pages at a time, and for login-required sites, we switch to browser mode. It’s fast, flexible, and doesn’t need ongoing maintenance or manual edits.
Jorge F.Inbound Sales ManagerThunderbit’s AI Autofill is a lifesaver. After scraping contact info, I use it to fill lead forms directly in my browser. I just select the tab, and it fills everything using the scraped row. No manual input needed.
Alina D.Freelance ResearcherI rely on Thunderbit for extracting data from PDFs, image-based sites, and infinite scroll pages. It handles messy formats with AI and delivers ready-to-export tables I can send to Google Sheets or Airtable in seconds.

Frequently Asked Questions

Extract Data using AI
Easily transfer data to Google Sheets, Airtable, or Notion
Chrome Store Rating
PRODUCT HUNT#1 Product of the Week
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