Pingrole Job Search

Search a continuously updated database of LinkedIn job listings across five markets. Filter by title, location, company, country, language, remote and contract type, and posting date. Each match returns structured job and company fields ready to export or pipe into your stack.

Coverage: Germany · Canada · United States · Netherlands · United Kingdom (LinkedIn only)

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Quick start (Apify Console)

1. Open this Actor in the Apify Console.
2. Go to the Input tab.
3. Fill in the four required fields: Job Title, Location, Country, and Limit.
4. Optionally set company, language, booleans, date range, skip, and sort.
5. Click Start.
6. When the run finishes, open the Dataset tab to browse results or download as JSON, CSV, Excel, or XML.

The four required fields (Job Title, Location, Country, Limit) open with default values you can edit before running. Optional fields like Skip and Sort use their own defaults.

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Input fields

Field	Required	Description
Job Title (title)	Yes	Default: software engineer. Partial, case-insensitive match. Comma-separated values are OR’d.
Location (location)	Yes	Default: toronto. Partial, case-insensitive match. Comma-separated OR supported.
Country (country)	Yes	Default: canada. Exact match: canada, germany, netherlands, United States, United Kingdom.
Company (company)	No	Partial match on company name. Comma-separated OR supported.
Language (language)	No	Exact match: en, fr, or de.
Remote	No	Checked = remote jobs only. Unchecked with explicit false in API = exclude remote. Leave empty to ignore.
Part Time	No	Part-time roles only (same true / false / ignore behavior).
Freelancer	No	Freelance roles only.
Academic	No	Academic roles only.
Research	No	Research roles only.
B2B	No	B2B contract roles only.
Date From (datetime_from)	No	Jobs scraped on or after this time. Formats: 2026-01-01 or 2026-01-01@11:00 (use @ instead of T for time).
Date To (datetime_to)	No	Jobs scraped on or before this time. Same format as Date From.
Limit	Yes	Default: 10. Number of jobs to return per run (1–100).
Skip	No	Offset for pagination (default 0).
Sort Field	No	datetime_from (newest/oldest by scrape time, default), title, company, language, or country.
Sort Direction	No	-1 = descending (newest first when sorting by date). 1 = ascending.

Boolean filters: In the Console, check a box to require that flag. In the API, use true to include only matching jobs, false to exclude them, or omit the field to ignore it.

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Example inputs

Software engineers in Toronto

{
  "title": "software engineer",
  "location": "Toronto",
  "country": "canada",
  "limit": 20
}

Remote data roles in Germany (German listings)

{
  "title": "data",
  "location": "Berlin",
  "country": "germany",
  "Remote": true,
  "language": "de",
  "limit": 50
}

Product roles at a specific company, posted in May 2026 (page 2)

{
  "title": "product manager",
  "location": "Amsterdam",
  "country": "netherlands",
  "company": "Booking",
  "datetime_from": "2026-05-01",
  "datetime_to": "2026-05-31",
  "limit": 10,
  "skip": 10,
  "sort_field": "datetime_from",
  "sort_direction": -1
}

Multiple title keywords (OR)

{
  "title": "backend, full stack, fullstack",
  "location": "London",
  "country": "United Kingdom",
  "limit": 25
}

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Output

Each run writes one dataset record per job to your run’s default dataset. Fields are omitted or null when not available on the listing.

Field	Description
title	Job title
company	Company name
location	Location string
country	Country
language	Listing language (en, fr, de, …)
job_type	e.g. fulltime, parttime
job_level	Seniority, e.g. mid-senior
job_url	LinkedIn job posting URL
description	Full job description text
timestamp	When the listing was scraped (UTC)
site	Source site (always linkedin for this Actor)
job_id	Stable job identifier
Remote, PartTime, Freelancer, Academic, Research, B2B	Job-type flags
salary_source, currency	Salary info when present
company_logo	Logo image URL
company_url	LinkedIn company page
company_url_direct	Company website
company_addresses	Company address data when available
company_industry	Industry
company_num_employees	Employee count range
company_revenue	Revenue band when available
company_description	Company description
company_rating	Company rating when available

The run also saves the same job array to the key-value store under OUTPUT (useful for API consumers that read KV store instead of the dataset).

Example record

{
  "title": "Software Engineer",
  "company": "Example GmbH",
  "location": "Berlin, DE",
  "country": "germany",
  "language": "de",
  "job_type": "fulltime",
  "job_level": "mid-senior",
  "job_url": "https://www.linkedin.com/jobs/view/4374072722",
  "description": "We are looking for...",
  "timestamp": "2026-05-16 14:50:09.053000",
  "site": "linkedin",
  "salary_source": null,
  "currency": null,
  "company_logo": null,
  "company_url": "https://linkedin.com/company/example-gmbh",
  "company_url_direct": "https://example.com",
  "company_addresses": null,
  "company_industry": "Software Development",
  "company_num_employees": "51-200",
  "company_revenue": null,
  "company_description": "Example GmbH is a Berlin-based...",
  "company_rating": null,
  "Remote": true,
  "PartTime": false,
  "Freelancer": false,
  "Academic": false,
  "Research": false,
  "B2B": false,
  "job_id": "li-4374072722"
}

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Pagination

Use Limit and Skip together to page through results:

Page	limit	skip
1	10	0
2	10	10
3	10	20

Each page returns at most limit jobs (max 100 per run). If a page returns fewer records than limit, you have reached the end of the matching set for that query. Run again with a higher skip to fetch the next page.

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Run from your code (Apify API)

Replace YOUR_ACTOR_ID with this Actor’s ID or username/name slug from the Apify Store.

Node.js

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' });

const run = await client.actor('YOUR_ACTOR_ID').call({
    title: 'software engineer',
    location: 'Toronto',
    country: 'canada',
    limit: 20,
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

Python

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("YOUR_ACTOR_ID").call(
    run_input={
        "title": "software engineer",
        "location": "Toronto",
        "country": "canada",
        "limit": 20,
    }
)
items = client.dataset(run["defaultDatasetId"]).list_items().items

cURL (start a run)

curl -X POST "https://api.apify.com/v2/acts/YOUR_ACTOR_ID/runs?token=YOUR_APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"title":"software engineer","location":"Toronto","country":"canada","limit":20}'

Fetch dataset items from the run’s defaultDatasetId in the API response, or download exports from the Console.

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Scheduling and integrations

In the Apify Console you can schedule this Actor (e.g. daily) so fresh jobs land in a dataset automatically. Connect the dataset to Google Sheets, Slack, Zapier, Make, Airtable, webhooks, or other Apify integrations without writing custom export code.

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Tips

• Start broad on Job Title and Location within your Country, then narrow with boolean flags and optional Company.
• Use Date From / Date To to focus on recently scraped listings.
• Sort by datetime_from with direction -1 for the newest jobs first.
• For large pulls, chain multiple runs with increasing skip (respect the 100-per-run cap).

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Support

Built by Hermann Samimi · Pingrole

• Live dashboard: realtime.pingrole.com
• Email: hermannsamimi@gmail.com
• Book a call: calendly.com/hermannsamimi/30min