Google Jobs Scraper

Scrape job listings from Google Jobs with location targeting, pagination control, and language/country filtering. Returns structured JSON with full job details, apply links, and highlights — ready for immediate use in pipelines or spreadsheets.

Python + MCP example: Apify-Google-Jobs-Scraper on GitHub

What This Actor Returns

Each dataset item is a single job listing with:

• Job basics — title, company name, location, source platform (via)
• Description — full job description text
• Highlights — structured qualifications, responsibilities, and benefits
• Extensions — raw tags like "Full-time", "3 days ago", "Health insurance"
• Detected extensions — parsed metadata: posted_at, schedule_type, benefits flags
• Apply options — direct application links (LinkedIn, Indeed, company site, etc.)
• Job ID — Google's unique identifier for the listing
• Search metadata — query, country, language, timestamp, pages processed

Use Cases

• Job market research — track hiring trends by role, location, or industry
• Recruiting pipelines — feed job data into ATS or CRM systems
• Salary and benefits benchmarking — aggregate compensation signals across listings
• Competitive intelligence — monitor which companies are hiring for specific roles
• Academic research — analyze labor market dynamics at scale

Input Parameters

Parameter	Type	Required	Default	Description
query	string	✅	—	Job search query (e.g., "Software Engineer", "Data Scientist in NYC")
location	string	❌	None	Location filter (e.g., "San Francisco, CA", "London, UK")
country	string	❌	None	Country code for search (e.g., us, gb, de)
language	string	❌	None	Language code (e.g., en, fr, es)
google_domain	string	❌	google.com	Google domain to use (e.g., google.co.uk)
num_results	integer	❌	100	Maximum number of job listings to return
max_pagination	integer	❌	0	Maximum pages to fetch. Set to 0 for unlimited (fetch all available results).
include_lrad	boolean	❌	false	Enable location radius search
lrad_value	string	❌	None	Radius in km when include_lrad is true (e.g., "25")
max_delay	integer	❌	1	Delay between page requests in seconds
cleanup_results	boolean	❌	true	Remove internal API metadata from output

Example Output

Each dataset item represents one job listing:

{
  "title": "Senior Software Engineer",
  "company_name": "Acme Corp",
  "location": "San Francisco, CA",
  "via": "via LinkedIn",
  "description": "We are looking for a Senior Software Engineer to join our growing team...",
  "extensions": ["Full-time", "3 days ago", "Health insurance", "Dental insurance"],
  "detected_extensions": {
    "posted_at": "3 days ago",
    "schedule_type": "Full-time",
    "health_insurance": true,
    "dental_coverage": true
  },
  "job_highlights": [
    {
      "title": "Qualifications",
      "items": ["5+ years of Python experience", "BS/MS in Computer Science or related field"]
    },
    {
      "title": "Responsibilities",
      "items": ["Design and build scalable backend services", "Collaborate with product and design teams"]
    }
  ],
  "apply_options": [
    { "title": "LinkedIn", "link": "https://www.linkedin.com/jobs/view/..." },
    { "title": "Indeed", "link": "https://www.indeed.com/viewjob?..." }
  ],
  "job_id": "eyJqb2JfdGl0bGUiOiJTZW5pb3IgU29mdHdhcmUgRW5naW5lZXIifQ==",
  "share_link": "https://www.google.com/search?q=Senior+Software+Engineer&ibp=htl;jobs&htidocid=...",
  "query": "Software Engineer",
  "location": "San Francisco, CA",
  "country": "us",
  "language": "en",
  "google_domain": "google.com",
  "search_timestamp": "2026-05-07T14:23:01.456789",
  "total_jobs_found": 87,
  "pages_processed": 9
}

Pricing

This actor uses pay-per-event billing — you only pay for what you use:

Event	Price	When charged
Setup	$0.20	Once per run
Page processed	$0.015	Per page of results (approx. 10 jobs/page)

Estimated costs:

• 10 jobs (~1 page): ~$0.215
• 100 jobs (~10 pages): ~$0.35
• 1,000 jobs (~100 pages): ~$1.70

The actor checks your budget before starting and will warn you if the estimated cost exceeds your limit.

How to Get Started

1. Go to the actor page on Apify and click Try for free
2. Enter your search query and optional location
3. Set num_results to control how many listings to retrieve
4. Click Run — results appear in the dataset within seconds
5. Export to JSON, CSV, or connect via the Apify API or MCP integration

Quickstart input:

{
  "query": "Software Engineer",
  "location": "San Francisco, CA",
  "num_results": 50
}

FAQ / Troubleshooting

No results returned?

• Check that your query is not empty
• Try removing the location filter — some queries return no results with overly specific locations
• Try setting country and language explicitly (e.g., "us" and "en")

Fewer results than expected?

• Google Jobs may have fewer listings than num_results for your query — this is normal
• Try broadening the query (e.g., "engineer" instead of "senior backend engineer")

Budget warning on startup?

• Increase your actor run budget limit in the run configuration
• Or reduce num_results / set a lower max_pagination limit

Actor exits immediately?

• Check that your run has a sufficient budget for at least 1 page + setup fee (~$0.215 minimum)

Missing fields in some listings?

• Not all Google Jobs listings include every field (salary, highlights, apply links vary by posting)
• Use additionalProperties in your integration to handle optional fields gracefully

Last Updated: 2026.06.02