Google Jobs Scraper — Multi-Board Apply Links, Salary & Employer Emails

Scrape Google's jobs vertical — the aggregated feed Google builds from LinkedIn, Indeed, Glassdoor, ZipRecruiter, Monster, Dice, Built In, Workday, Greenhouse, Lever and thousands of company career sites. One search surfaces postings from all of them at once.

Every row carries the job's title, company, location, source board, posted date, salary, schedule, benefits — and every syndicated apply link Google knows about, not just one.

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Why use this scraper

Every apply route, not one	Google lists the same job on LinkedIn and Indeed and the employer's own ATS. Most scrapers return a single link. This one returns all 4–8, each labelled with its board.
Full descriptions, structured	Not just a teaser: the complete job description (median ~3,500 characters) plus Google's own qualification, responsibility and benefit bullets as clean arrays.
New-jobs-only monitoring	Turn on one checkbox and the actor remembers what it already sent you. Schedule it daily and every run returns only the postings that are new — no re-reading yesterday's list, and no paying for duplicate rows.
Employer contact emails	Optional: resolve the hiring company's own website and pull a public contact address, turning a job feed into a lead list.
Goes past the 10-result cap	Google's jobs tab visibly stops at ~10 results. This actor follows Google's own "load more" cursor to fetch further pages — up to 10 pages (~100 jobs) per search, something the visible page never offers.
Built for breadth	On top of paging, your keywords × locations expand into a full search matrix run in parallel, then de-duplicated.
One consistent row shape	Identical field names to the rest of this jobs-scraper family, so one column mapping works across all of them.

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Overview

Google's jobs vertical (the "Jobs" tab, internally udm=8) is the largest job aggregator most people never scrape directly — because it will not render without JavaScript and blocks datacenter traffic outright. This actor handles that for you and returns clean, structured rows.

Give it a list of keywords and a list of locations. It builds one Google search per combination, fetches them concurrently, parses each result card, merges everything, drops duplicates, and writes one row per job.

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Supported inputs

Input	Example	Notes
Keywords	software engineer, registered nurse	Job titles, skills, or free text
Locations	New York, Chicago, London	Required in practice — see the FAQ
Country	us, gb, ca, au, in	Which Google market to search
Google Jobs URLs	https://www.google.com/search?q=nurse+jobs+in+chicago&udm=8	Paste directly; legacy ibp=htl;jobs links are upgraded automatically

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Use cases

• Job boards & aggregators — fill a niche board from a source that already merges every major board.
• Recruitment agencies — monitor who is hiring for your specialty in your city, daily, and see which ATS each employer uses.
• Sales & lead generation — companies that are hiring are companies that are spending. Turn on email enrichment and every posting becomes a qualified lead with a contact address.
• Market & salary research — track posting volume, salary bands and remote share by role and metro over time.
• Candidate tools — power a job-alert product with a de-duplicated, multi-board feed.
• HR & competitive intelligence — watch a competitor's hiring: which roles, which locations, which salary bands.

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How it works

1. Expand — your keywords × locations become a matrix of Google searches.
2. Fetch — each search is rendered server-side through a built-in unblocking service, from a residential exit node in your chosen country. Nothing to configure.
3. Parse — each result card yields title, company, location, source board, posted date, salary, schedule, benefits and qualifications.
4. Attribute — Google renders each job's apply links in its own container; the actor matches them 1:1 to the right job, so links never bleed between postings.
5. De-duplicate — the same job found by two different searches is emitted once.
6. Filter — recency, salary-only, remote-only and schedule filters are applied.
7. Enrich (optional) — resolve the employer's website and scrape a public contact email.
8. Push — one clean row per job.

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Input configuration

Field	Type	Default	Description
keywords	array	["software engineer"]	Job titles / keywords to search
locations	array	["New York", "San Francisco"]	Cities or regions. Strongly recommended
country	select	us	Google market (gl). See the EU note in the FAQ
language	string	en	Google interface language (hl)
googleDomain	string	—	e.g. google.co.uk
startUrls	array	—	Paste Google Jobs URLs directly
Google-side filters			applied before Google's ~10-result cut
datePosted	select	—	today / 3days / week / month
employmentTypes	array	—	FULLTIME / PARTTIME / CONTRACTOR / INTERN — also widens coverage
workFromHome	boolean	false	Google's own remote filter
radius	integer	—	Miles around the location
Client-side filters			applied to what Google returned
postedWithinHours	integer	—	Keep only jobs posted in the last N hours
salaryOnly	boolean	false	Keep only jobs that display a salary
remoteOnly	boolean	false	Keep only remote-looking jobs
scheduleTypes	array	—	e.g. Full-time, Contractor
companyFilter	array	—	Only these employers
excludeCompanies	array	—	Drop these employers (e.g. staffing agencies)
viaFilter	array	—	Only jobs from these source boards
onlyNewJobs	boolean	false	Emit only postings not seen in previous runs
enrichEmails	boolean	false	Find employer contact emails
qualifyByPayment	boolean	false	Flag employers that take payments online
maxPagesPerQuery	integer	3	Result pages per search (1–10), ~10 jobs each
maxItems	integer	1000	Stop after this many jobs
maxConcurrency	integer	10	Parallel Google searches

Getting more than 10 jobs per search

Google's jobs tab shows ~10 results and offers no page 2 — but this actor gets past that two ways, and they multiply:

1. Pages per search (maxPagesPerQuery, default 3): the actor follows Google's own "load more" mechanism to fetch additional result pages. Each page returns ~10 different jobs — in testing, 3 pages on one keyword and city produced 30 unique jobs with zero overlap.
2. The search matrix: keywords × locations × employmentTypes each add distinct searches. Employment types are especially effective — each type returns a largely different result set (FULLTIME + CONTRACTOR doubled results with zero overlap in testing).

Combined: 3 keywords × 4 cities × 3 pages ≈ 360 jobs.

Example input

{
  "keywords": ["software engineer", "data analyst"],
  "locations": ["New York", "Chicago", "Austin"],
  "country": "us",
  "postedWithinHours": 24,
  "onlyNewJobs": true,
  "maxItems": 500
}

That is 2 × 3 = 6 searches, filtered to the last 24 hours, returning only jobs no previous run has seen.

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Output overview

One row per job. Fields the source does not provide are null (or []) rather than missing, so your columns never shift.

Output sample

{
  "type": "job",
  "source": "google-jobs",
  "jobId": "lead software engineer java aws|jpmorganchase|new york ny",
  "title": "Lead Software Engineer: Java/AWS",
  "companyName": "JPMorganChase",
  "location": "New York, NY",
  "remote": false,
  "via": "LinkedIn",
  "postedRaw": "12 hours ago",
  "postedDate": "2026-07-25T09:26:48.375Z",
  "salary": {
    "currency": "USD",
    "min": 152000,
    "max": 215000,
    "raw": "152K–215K a year",
    "unit": "YEAR"
  },
  "salaryRaw": "152K–215K a year",
  "contractType": "Full-time",
  "employmentTypes": ["Full-time"],
  "benefits": ["Health insurance", "Dental insurance"],
  "qualifications": [],
  "applyType": "external",
  "applyUrl": "https://www.linkedin.com/jobs/view/lead-software-engineer-java-aws-at-jpmorganchase-4445316605?utm_campaign=google_jobs_apply",
  "applyLinks": [
    { "board": "LinkedIn",       "url": "https://www.linkedin.com/jobs/view/..." },
    { "board": "JPMorgan Chase", "url": "https://jpmc.fa.oraclecloud.com/hcmUI/CandidateExperience/..." },
    { "board": "Indeed",         "url": "https://www.indeed.com/viewjob?jk=88e34225b97d1f3a..." },
    { "board": "Built In NYC",   "url": "https://www.builtinnyc.com/job/lead-software-engineer-java-aws/..." }
  ],
  "applyLinkCount": 8,
  "searchKeyword": "software engineer",
  "searchLocation": "New York",
  "searchCountry": "us",
  "scrapedAt": "2026-07-25T21:26:52.983Z"
}

Key output fields

Field	Type	Description
title	string	Job title
companyName	string	Hiring employer
location	string	As shown by Google, e.g. New York, NY
remote	boolean	Inferred from the title and location
via	string	The board Google syndicated this posting from
postedDate	ISO date	Absolute date derived from Google's "12 hours ago"
postedRaw	string	Google's original relative wording
salary	object	{ currency, min, max, raw, unit }
contractType	string	Full-time, Contractor, Internship, …
description	string	Full job description text — median ~3,500 characters
qualifications	array	Requirement bullets, as identified by Google from the original post
responsibilities	array	Duty bullets from the same source
benefits	array	e.g. Health insurance, 401(k)
applyLinks	array	Every apply route, each with its board name
applyUrl	string	The primary apply link (the via board where possible)
contactEmail	string	Employer email — only with enrichEmails
contactWebsite	string	Employer website — only with enrichEmails
searchKeyword / searchLocation	string	Which of your searches produced this row

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FAQ

How many jobs will I get per search? Up to ~10 per page × maxPagesPerQuery (default 3, max 10) — so ~30 per search by default, up to ~100. Google's own interface stops at 10; the extra pages come from the same "load more" mechanism the interface uses, fetched for you automatically. For even more volume, widen the matrix: 5 keywords × 6 cities × 3 pages ≈ 900 jobs.

Should I use the Google-side or the client-side filters? Prefer the Google-side ones (datePosted, employmentTypes, workFromHome, radius). Because Google only returns ~10 results, filtering there changes which jobs you receive; filtering afterwards only throws away rows you already paid for. Asking Google for "past 24 hours" returns 10 fresh jobs; asking for anything and then filtering to 24 hours might leave you 2.

Do I have to provide a location? In practice, yes. Google's jobs vertical usually answers a bare keyword with "there aren't any Jobs matches on this topic". Add a location and the same keyword returns a full set. The actor warns you in the log if you omit locations.

Why do I get no results for Germany / France / Spain? Google has wound its jobs widget down across the EU, and those markets now return nothing at all. This is Google's change, not a fault in the actor — the log warns you when you pick an affected country. The US, UK, Canada, Australia and India all return rich results.

Why is salary empty on many rows? Because Google only displays a salary when the source posting includes one — roughly 30% of the time in our testing. The salaryOnly filter keeps just those rows if you need complete compensation data.

Does the email enrichment find an address for every employer? No, and it is honest about that. It resolves the employer's website from the company name and reads its public contact pages. Large corporations (Amazon, Charles Schwab) usually publish no contact email, so contactEmail will be empty even though contactWebsite is filled. Hit rates are much better on small and mid-sized employers.

How does "only new jobs" decide what is new? A job's identity is its title + company + location. Once emitted, it is remembered for 45 days in the actor's key-value store, then forgotten — so a genuine re-posting months later reaches you again. The first run returns everything; every run after that returns only what changed.

Do I need a proxy? No. Google is fetched through a built-in unblocking service with no configuration. The proxy input is used only by the optional email-enrichment step.

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Support

Found a bug or want a field added? Open an issue on the actor's Issues tab and I will take a look.

Additional services

Need this customised — a specific country, extra fields, a private variant, or a different delivery format? Get in touch through the Apify Store profile.

Explore more scrapers

This actor is part of a large family of job-board scrapers sharing the same output shape: LinkedIn Jobs, Indeed, ZipRecruiter, Glassdoor, Dice, SimplyHired, Seek, StepStone, Reed, TotalJobs, Workday, Greenhouse, Lever, Ashby, BambooHR, SmartRecruiters and many more.

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🤖 For AI agents & LLM apps

This actor is a clean tool call for agents that need live labour-market data.

• Deterministic input — keywords and locations are plain string arrays; no URL construction required.
• Stable schema — every row has the same keys in the same order, with null instead of missing fields, so parsing never breaks.
• Structured salary — salary.min / salary.max / salary.currency are already numbers and codes, no regex needed downstream.
• Idempotent scheduling — onlyNewJobs: true gives an agent a change feed instead of a full snapshot, so memory stays small and tokens stay cheap.
• Provenance built in — searchKeyword, searchLocation and via let an agent explain exactly where each row came from.

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⚠️ Disclaimer

This actor collects only publicly available information displayed on Google search result pages. It does not log in, does not bypass any paywall, and does not access private or personal data.

Job listings and their content remain the property of their respective sources and employers. You are responsible for ensuring your use of the scraped data complies with Google's Terms of Service, the source boards' terms, and all applicable laws in your jurisdiction — including GDPR, CCPA and equivalent data-protection regulations where relevant. This tool is provided for legitimate research, recruitment and market-analysis purposes.

Google's jobs vertical is a third-party surface that can change or be withdrawn at any time — as already happened across the EU. Availability and field coverage may vary by country and over time.

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