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Let's turn one public LinkedIn job into a useful record.

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We'll run the Neuton Job Details Actor once, inspect the

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result, then export a checked CSV.

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Open the Actor on Apify and read the current Pricing

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tab. You need an Apify account, but no LinkedIn login.

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Set a charge limit before starting.

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In Input, open the JSON editor. Leave job URLs empty,

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enter data engineer and London, and set max results to

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one. The Actor finds a current public listing at run time.

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Select Start once. When the run finishes, open Dataset. A

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succeeded run can still have zero useful rows, so check the data itself.

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Check job ID and URL, then title, company, location, description,

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and application path against the public listing. The row on

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screen is illustrative. Missing salary stays null.

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If the Dataset is empty, open Storage, the default key-value

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store, and Run Summary. Check its failed inputs and rows

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saved. The Log has further diagnostics.

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Once the row passes review, export Dataset as CSV. Open

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the file and verify job ID and source URL before

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sending it to a spreadsheet.

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That's the workflow: one bounded input, one checked row, one

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export. Links to the Actor and full guide are below.

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Review live pricing before your own run.