How do you deliver job offers data as an external feed to clients?

Job offers data is typically delivered as an external feed using structured formats such as JSON, XML, or CSV, transmitted either through a dedicated API endpoint or via scheduled file exports. The right delivery method depends on how the client’s system consumes data and how frequently the listings need to be refreshed. Below, we walk through the key questions around building and delivering a reliable job offers data feed to clients.

What formats are used to deliver job offers data as a feed?

The most common formats for delivering a job offers data feed are JSON, XML, and CSV. JSON is widely preferred for API-based integrations because it is lightweight, easy to parse, and natively supported by most modern programming languages. XML remains popular in enterprise and government environments where strict schema validation is required. CSV works well for simpler bulk exports where the client processes data in spreadsheets or legacy systems.

Beyond file format, the structure of the data matters just as much. A well-designed job feed typically includes standardized fields such as job title, employer name, location, employment type, salary range, publication date, expiration date, and a unique identifier for each listing. Consistent field naming across sources makes it far easier for clients to ingest the feed directly into their own platforms, applicant tracking systems, or job aggregators without heavy data transformation on their end.

For clients who need real-time or near-real-time access, delivering the feed through a REST or GraphQL API endpoint is the most flexible approach. The client queries the endpoint on demand and retrieves only the records they need, filtered by location, category, or date. For clients with simpler requirements, a scheduled file drop to an SFTP server or cloud storage bucket works reliably and requires minimal infrastructure on either side.

How does a crawling service collect job listings from multiple sources?

A crawling service collects job listings by systematically visiting career pages, job boards, and employer websites, extracting structured data from each page, and consolidating it into a single normalized dataset. The crawler follows links, handles pagination, and identifies the HTML or JSON-LD patterns that contain job data, then maps those fields to a unified schema before storing or forwarding the results.

Collecting from multiple sources introduces significant complexity. Each source has its own page structure, URL patterns, and update frequency. A robust web scraping setup for job data handles these differences through source-specific extraction rules, often called scrapers or spiders, that are maintained independently. When a source changes its layout, only that spider needs updating rather than the entire pipeline.

Modern crawling services also handle practical challenges such as JavaScript-rendered pages, login-protected listings, rate limiting, and duplicate detection. Deduplication is especially important in job data because the same vacancy often appears on multiple boards simultaneously. A good pipeline assigns a canonical record to each unique job posting and merges or discards duplicates before the data reaches the client feed.

What’s the difference between a push feed and a pull feed for job data?

A push feed delivers job data to the client automatically at scheduled intervals or when new records are available, without the client needing to request it. A pull feed requires the client to actively query an endpoint to retrieve the latest data. The core difference is who initiates the data transfer: the provider pushes, or the client pulls.

Push feed delivery

With a push feed, the data provider sends updated job listings to a client-specified endpoint, email address, or storage location on a fixed schedule or triggered by new content. This works well when the client’s system needs to stay in sync passively, for example ingesting a nightly batch of new and expired listings into a recruitment platform. Push feeds are straightforward to set up but offer less flexibility if the client needs on-demand access or wants to filter results dynamically.

Pull feed delivery

A pull feed, typically implemented as a job listings API, gives the client full control over when and what they retrieve. The client sends a request with parameters such as location, job category, or date range, and the API returns matching records instantly. Pull feeds suit use cases where the client’s application displays live search results or needs to react to user input in real time. The tradeoff is that the client must manage API authentication, handle rate limits, and build the integration on their side.

How do you keep a job offers feed accurate and up to date?

Keeping a job offers feed accurate requires continuous re-crawling of source pages, automated expiry detection, and a validation layer that flags anomalies before they reach the client. Job listings have a short shelf life; a vacancy posted on Monday may be filled or removed by Thursday. Without frequent refresh cycles, a feed quickly fills with stale or duplicate records that erode client trust.

The refresh strategy should match the source’s update frequency. High-volume job boards that publish hundreds of new listings per hour need crawling intervals measured in minutes. Smaller employer career pages may only need daily or weekly checks. Prioritizing crawl frequency by source activity reduces infrastructure costs while keeping data freshness where it matters most.

Expiry management is equally important. When a listing disappears from the source, the feed should mark it as expired or remove it within the next crawl cycle rather than leaving it active indefinitely. Some feeds include an explicit expiration date field supplied by the source; others rely on the crawler to detect a 404 response or the absence of the listing on a subsequent visit. Both approaches need to be handled in the pipeline logic to avoid delivering dead listings to clients.

What legal considerations apply when delivering job data to clients?

When delivering job data as an external feed, the key legal considerations are terms of service compliance for each source, GDPR obligations when personal data is involved, and intellectual property rights over the compiled dataset. Ignoring any of these exposes both the data provider and the client to legal risk.

Most job boards and career pages publish terms of service that restrict automated data collection. Before crawling any source, it is essential to review those terms and assess whether scraping is permitted, restricted to specific use cases, or prohibited entirely. Some platforms offer official data partnerships or licensed feeds as an alternative to scraping, which provides a legally cleaner route to the same data.

GDPR applies whenever the job listings contain personal data, which can include recruiter contact details, named hiring managers, or any other identifiable information embedded in the posting. Under GDPR, personal data must have a lawful basis for processing, be minimized to what is necessary, and not be retained longer than needed. Clients receiving the feed also become data processors or controllers in their own right, so the data-sharing arrangement should be documented in a data processing agreement that clearly defines responsibilities on both sides.

Finally, the compiled dataset itself may attract database rights under EU law, meaning the organization that invested substantially in collecting and organizing the data holds rights over its distribution. Contracts with clients should specify permitted uses, redistribution restrictions, and attribution requirements to protect those rights and avoid downstream misuse of the feed.

How Openindex helps with job offers data feed delivery

We specialize in building and delivering job offers data feeds tailored to the exact needs of your platform or application. Whether you need a real-time pull API, a scheduled push export, or a fully managed data pipeline that handles crawling, normalization, deduplication, and refresh cycles, we cover the entire process so you receive clean, structured data without the operational overhead.

Here is what working with us looks like in practice:

• Multi-source crawling: We collect job listings from career pages, job boards, and aggregators using source-specific extraction rules that we maintain and update as sites change.
• Format flexibility: We deliver feeds in JSON, XML, or CSV through an API endpoint, SFTP, or cloud storage, depending on how your system consumes data.
• Freshness management: We configure crawl frequencies and expiry logic to match the update patterns of each source, keeping stale listings out of your feed.
• Legal compliance: We operate within GDPR requirements and source terms of service, and we document data-sharing arrangements clearly so your legal exposure is minimized.
• Scalability: Our infrastructure handles millions of URLs and scales with your volume requirements without performance degradation.

If you are ready to receive reliable, structured job data without building and maintaining the collection pipeline yourself, get in touch with us to discuss what a tailored data feed solution looks like for your use case.