SEEK Jobs Scraper

SEEK Jobs Scraper: jobs from Australia and New Zealand, with the pay as written

Search SEEK by keyword and location and get one row per job. Title, company, where it is, whether it is remote, hybrid or on-site, employment type, the posting date, the teaser and the link. No login, no cookies, no API key.

Salary is the part worth understanding before you build a report on it. SEEK lets the advertiser type the pay in free text, so one search comes back with $130K - $160K + Super sitting next to Rewarding hourly rates $$$. The label is kept exactly as written, and salaryMin and salaryMax are pulled out of it when there are numbers to pull.

includeDetails is not returning details at the moment. Rows still come back with everything the search card carries, plus a detailsError, but no description.

🔍 What SEEK Jobs Scraper does

One actor covers both SEEK sites. site picks AU or NZ, and the rest of the input works the same either way.

It runs your search, pages through the results, and deduplicates on job ID. You can also hand it job IDs or job URLs directly, and those are merged with the search results rather than duplicating them.

datePosted, workTypes, workplaceTypes and salaryMin are applied to the rows after they come back, not by SEEK. So they narrow what you receive, and a tight filter on a broad search can leave you with far fewer rows than maxItems. Widen maxPages when that happens.

minApplicants runs after the fetch too, and it is slower. The search results carry no applicant count, so each job that passes your other filters is checked on its own, up to twice maxItems a run.

sortBy works the other way round. SEEK does the sorting itself, so date really starts at the newest listing and pages back from there. SEEK also pins up to two sponsored ads to the top of every page, whatever their age. With date they are kept but moved to where their own listingDate puts them, so a small run can end with an older sponsored job or two.

📥 What you give it

{
  "site": "NZ",
  "keywords": "data analyst",
  "location": "Auckland",
  "workplaceTypes": ["Remote"],
  "datePosted": "7days",
  "maxItems": 100
}

If you feed jobIds or jobUrls with includeDetails off, the row comes back holding only the ID and the URL, and it is charged. The job page is never opened, so the title and company stay null, and an ID that does not exist is billed the same as one that does. Turn descriptions on when you feed IDs directly.

salaryMin drops every job whose salary could not be parsed, which on SEEK is a lot of them. Use it to shortlist, not to survey a market.

📤 What you get back

A real row from a recent run, with the teaser cut short:

{
  "ok": true,
  "site": "AU",
  "jobId": "94483533",
  "title": "Graduate Software Engineer",
  "company": "Arturia AI",
  "location": "Macquarie Park, Sydney NSW",
  "workplaceType": "On-site",
  "employmentType": "Full time",
  "salary": null,
  "salaryMin": null,
  "salaryMax": null,
  "listingDate": "2026-09-08T03:09:03Z",
  "teaser": "Graduate Software Engineer ...",
  "bulletPoints": [],
  "url": "https://www.seek.com.au/job/94483533",
  "source": "seek-api"
}

With includeDetails on, rows also carry description, requirements, education, experience, validThrough, datePosted and hiringOrganization, plus detailsError when that page could not be read. Detail fetching is best effort: a row stays useful when an employer's page has changed or gone.

🧾 Reading the output

Three kinds of row can land in your dataset.

Filter on _sample being absent, not on ok. The sample row is ok: true and looks like a real job in the table, which is exactly how it slips into a pipeline.

Diagnostics carry code, not errorCode:

▶️ How to run it

1. Open SEEK Jobs Scraper and click Try for free. 2. Pick SEEK site, Australia or New Zealand. 3. Type your terms into Keywords and a city into Location. 4. Leave Maximum jobs at 50 for a first run, then click Start. 5. Download the dataset as JSON, CSV or Excel, or read it from the Apify API.

💰 How much does it cost?

$0.81 per 1,000 jobs. Flat on every Apify plan, no volume tiers.

You pay per job row delivered. Duplicates across search and direct IDs, jobs your filters removed, the sample row and diagnostic rows are all free, and switching descriptions on costs nothing extra per job.

💡 What people use it for

• Recruiters pricing a role against what is actually being advertised this week, reading salary

rather than the parsed numbers.

• Job boards pulling Australian and New Zealand listings on a schedule and deduplicating on

jobId.

• Tracking how many remote roles a sector is posting, using workplaceTypes across repeat runs.
• Watching a shortlist of employers by running their name as the keyword.
• Pulling full adverts with includeDetails to see which skills keep appearing.

🚧 What it does not do

• Australia and New Zealand only. No other SEEK market, and no other job board.
• No logins, no applications. It reads public listings and does not apply to anything.
• No candidate data. Job adverts only.
• Salary parsing is rough by nature, because the source is free text. Numbers that are not pay

can end up in salaryMin.

• 1,000 jobs per run is the ceiling. For more, split by location, by keyword, or run AU and NZ

separately.

• Filters run after the fetch, so a narrow filter on a broad search returns few rows unless you

raise maxPages.

• Rows land at the end of the run. If a search page fails partway through, the run finishes with

a diagnostic and the jobs already collected do not arrive. Re-run it, ideally smaller.

🧭 Which jobs scraper do you need?

❓ Questions people ask

Do I need a SEEK account? No. A keyword is enough.

Does it cover New Zealand? Yes. Set site to NZ.

Why is salary null on so many rows? Because the advertiser did not publish pay. SEEK does not require it, and a large share of listings leave it out.

Why did salaryMin cut my results in half? It only keeps jobs whose pay could be read as numbers. Adverts that say "competitive" have nothing to compare.

How many jobs can one run return? Up to 1,000, with the default at 50.

Is scraping job listings legal? These are public job adverts. They can name real people, which GDPR and similar laws cover, so have a reason for collecting them, and keep to SEEK's terms and a sensible request rate. Apify's write-up on scraping and the law is a good place to start, and we are not lawyers.

🆘 If something breaks

Open the Issues tab on the actor page. Send the site, the keywords and the run ID. The code on the diagnostic row usually names the problem on its own.