Google Jobs Scraper Pro — Real-Time Job Data

The most reliable Google Jobs scraper on Apify. Extract structured job listings from Google's jobs carousel at scale — including full descriptions, salary ranges, apply links, qualifications, and benefits.

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Why this scraper?

Most Google Jobs scrapers on Apify have sub-2/5 ratings because they use brittle CSS selectors, ignore dynamic rendering, and break within days of a Google UI update. Google Jobs Scraper Pro is built differently:

• Multi-selector fallback chains — every data field has 4–6 selector fallbacks so minor Google DOM changes don't break extraction
• Playwright + stealth — full headless Chrome automation with fingerprint masking and realistic browser headers
• Proper detail panel handling — clicks each job card to open the full detail pane before extracting long-form data (description, qualifications, benefits)
• Smart pagination — automatically loads more jobs until your maxJobsPerQuery limit is reached
• PAY_PER_EVENT billing — you only pay for jobs actually extracted, never for failed or empty requests

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Use cases

Use case	Description
Job aggregation	Build a job board that pulls real-time listings from Google Jobs across any market
Salary research	Collect salary ranges from thousands of postings to benchmark compensation
HR tech integration	Feed structured job data into ATS platforms, analytics dashboards, or ML pipelines
Recruitment automation	Monitor competitors' hiring activity or track open roles at target companies
Labour market analytics	Analyse demand for skills, job titles, or locations over time
Academic research	Gather large datasets of job postings for NLP or economics research

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Input

{
    "queries": ["software engineer London", "data scientist remote"],
    "country": "gb",
    "language": "en",
    "maxJobsPerQuery": 100,
    "datePosted": "week",
    "jobType": "fulltime",
    "remoteOnly": false,
    "proxyConfiguration": {
        "useApifyProxy": true,
        "apifyProxyGroups": ["RESIDENTIAL"]
    }
}

Input fields

Field	Type	Default	Description
queries	string[]	required	Search queries, e.g. ["nurse London", "python developer remote"]
country	string	"us"	ISO 3166-1 two-letter country code for localising results
language	string	"en"	ISO 639-1 two-letter language code
maxJobsPerQuery	integer	50	Max jobs to collect per query (1–500)
datePosted	string	"any"	Filter by posting date: any, today, 3days, week, month
jobType	string	(any)	Filter by employment type: fulltime, parttime, contractor, internship, temporary
remoteOnly	boolean	false	Append "remote" to every query to target remote positions
proxyConfiguration	object	(none)	Apify Proxy or custom proxy config — residential proxies strongly recommended

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Output

Each job listing is saved as a dataset item with the following schema:

{
    "title": "Senior Software Engineer",
    "company": "Monzo",
    "location": "London, UK (Hybrid)",
    "description": "We are looking for a Senior Software Engineer to join our Platform Engineering team...",
    "salary": "£90,000 – £130,000 a year",
    "jobType": "Full-time",
    "datePosted": "3 days ago",
    "applyUrl": "https://boards.greenhouse.io/monzo/jobs/5678901",
    "source": "LinkedIn",
    "qualifications": [
        "5+ years of experience with Go or a similar compiled language",
        "Experience with distributed systems and microservices",
        "Strong understanding of system design principles"
    ],
    "benefits": [
        "Stock options",
        "Private health insurance",
        "Flexible working"
    ],
    "jobHighlights": [
        "Hybrid — 2 days in office",
        "90k–130k annually",
        "Full-time"
    ],
    "query": "software engineer London",
    "scrapedAt": "2026-04-01T10:00:00.000Z"
}

Output fields

Field	Type	Description
title	string	Job title
company	string	Hiring company name
location	string	Office location or remote designation
description	string	Full job description (may include HTML)
salary	string | null	Salary range if provided, otherwise null
jobType	string | null	Employment type (Full-time, Part-time, Contract, etc.)
datePosted	string | null	Human-readable posting date (e.g. "3 days ago")
applyUrl	string | null	Direct application URL (company ATS or job board)
source	string | null	Where the listing was posted (LinkedIn, Indeed, company site, etc.)
qualifications	string[]	Required/preferred qualifications bullet points
benefits	string[]	Benefits and perks
jobHighlights	string[]	Key job highlights shown at the top of the detail panel
query	string	The search query that produced this listing
scrapedAt	string	ISO 8601 timestamp of when the record was extracted

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Pricing

$1.00 per 1,000 jobs (PAY_PER_EVENT)

You are charged only for jobs successfully extracted and pushed to the dataset. Empty results, failed pages, and pagination requests are not charged.

Estimated costs for common workflows:

Workflow	Jobs	Cost
Quick search (1 query, 50 jobs)	50	~$0.05
Standard run (5 queries, 100 jobs each)	500	~$0.50
Large-scale collection (20 queries, 200 each)	4,000	~$4.00
Monthly market analysis (100 queries, 100 each)	10,000	~$10.00

Proxy costs are additional if using Apify Proxy. Residential proxies reduce blocking risk but cost more. For best reliability, use Residential proxy groups.

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Technical details

How it works

1. URL construction — builds a Google Jobs search URL: https://www.google.com/search?q={query}&ibp=htl;jobs&hl={lang}&gl={country}
2. Page load — navigates with full headless Chromium, applies stealth patches and rotates User-Agents from a pool of 7 real Chrome versions
3. Job card iteration — locates all job card <li> elements in the Google Jobs panel
4. Detail extraction — clicks each card to open the right-side detail panel, then extracts all structured fields using multi-fallback selectors
5. Pagination — clicks "More jobs" button repeatedly until maxJobsPerQuery is reached or no more results exist
6. PAY_PER_EVENT charging — charges job-result event for each record pushed to the dataset

Anti-detection

• Headless Chrome with --disable-blink-features=AutomationControlled
• navigator.webdriver masked
• Realistic User-Agent, Accept-Language, Sec-Ch-Ua headers
• Viewport randomisation (1280–1480 × 900–1000px)
• Crawlee fingerprint generator (desktop Chrome 110+, Windows/macOS)
• Random delays between 800ms–2200ms between actions
• Cookie consent banner auto-dismissal

Error handling

• Automatic retry up to 3 times per URL
• CAPTCHA / "unusual traffic" detection with error logging
• Per-field fallback selectors survive minor Google DOM changes
• Gracefully skips cards where extraction returns empty data

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Requirements

• Node.js >= 18
• Apify SDK v3
• Playwright >= 1.42
• Recommended: Apify Residential proxies for large runs

Local development

git clone <repo>
cd google-jobs-scraper-pro
npm install
npx playwright install chromium
npm run dev

Create a storage/key_value_stores/default/INPUT.json file with your input before running locally.

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Changelog

v1.0.0

• Initial release
• Full Google Jobs extraction: title, company, location, description, salary, job type, date posted, apply URL, source, qualifications, benefits, highlights
• PAY_PER_EVENT billing at $1.00 / 1,000 jobs
• Stealth mode with fingerprint rotation
• Pagination support via "More jobs" button
• Support for country, language, date posted, job type, and remote-only filters

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Related actors

• LinkedIn Jobs Scraper — extract jobs from LinkedIn
• Indeed Scraper — scrape Indeed.com job listings
• Glassdoor Scraper — jobs + company reviews

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Built with Apify SDK v3 and Crawlee.