InfoJobs Spain Job Listings Scraper

InfoJobs Job Scraper 🇪🇸 is an evidenced Store rival with a Spain-focused promise to extract job titles, descriptions, and company details for market analysis and recruitment research. This actor addresses the same buyer intent with a more explicit workflow around configurable queries or startUrls, bounded runs, proxy settings, and inspection of reusable Apify dataset records; it does not claim broader country coverage or richer fields than the source returns.

Brazil Jobs Scraper — InfoJobs, Vagas, Gupy, LinkedIn is another evidenced rival, positioned around combining five Brazilian job boards and fields such as salary, benefits, experience level, and work model. That breadth is useful for cross-board Brazilian research, while this actor is intentionally narrower and better suited to buyers who need focused InfoJobs collection, repeatable search inputs, and a clearly documented validation step instead of an unsupported promise of multi-board coverage.

What this actor does

The actor collects job-search results from InfoJobs and writes structured records to the Apify dataset. It is suitable for:

• Recruitment research and talent-market discovery.
• Comparing recurring searches by role, company, or location.
• Employment and job-market monitoring.
• Building a bounded input dataset for spreadsheets, warehouses, or internal automation.
• Exporting collected records as JSON or CSV after review.

The available inputs are:

• queries — search terms or query definitions accepted by the current actor schema.
• startUrls — InfoJobs search URLs to collect.
• maxItems — an upper bound for a run.
• proxyConfiguration — proxy settings appropriate for the access environment.

Always open the current input schema before running. Input names, accepted shapes, and returned fields are implementation details and may change.

Recommended workflow

1. Start with one narrowly scoped query or search URL.
2. Set a small maxItems value for validation.
3. Configure a suitable proxy only when required by the source or your operating environment.
4. Run the actor and inspect several dataset records.
5. Confirm which title, description, company, location, salary, and URL fields are present for your search.
6. Adjust the query or limit, then export the verified dataset or connect it to downstream processing.
7. For monitoring, retain the query, URL, run date, and filtering choices so later runs remain comparable.

Output and dataset use

The run writes records to the default Apify dataset. The exact schema depends on the source response and actor implementation, so treat sample records from your own run as the source of truth. Records can be reviewed in Apify and exported to JSON or CSV. Do not build a production integration around an assumed field until it has been observed in representative results.

Limitations and responsible use

The actor does not guarantee complete coverage of InfoJobs, a fixed number of results, real-time freshness, stable fields, or uninterrupted execution. Results can vary with query wording, search availability, pagination, response changes, access conditions, proxy behavior, and source-side restrictions. A failed or partial run should be reviewed rather than interpreted as proof that no matching jobs exist.

Use only data and access methods you are permitted to use. Respect InfoJobs terms, applicable laws, privacy requirements, rate limits, and any restrictions on storing or redistributing job or personal information. This actor is a collection tool, not a guarantee that a listing is current, genuine, available, or suitable for a hiring decision.

Quick-start example

Review the current schema, provide a focused query or InfoJobs search URL, set maxItems to a conservative test value, and run the actor. Inspect the resulting dataset before scaling the run or automating an export.