FAQ
Refresh rate
Available formats
Delivery frequency
Ongoing*
JSON and CSV
Daily, monthly, quarterly
*📌 We update Professional Network Jobs continuously throughout the month.
The number of updated jobs varies monthly, as we can only update jobs that are still available on Indeed.
We send the professional network data using the following methods:
Method | Description |
|---|---|
Links | We provide you with the link and login credentials for you to retrieve the data |
Amazon S3 | Provide your storage credentials, and we will send the data to you |
Google Cloud | Provide your storage credentials, and we will send the data to you |
Microsoft Azure | Provide your storage credentials, and we will send the data to you |
We deliver data in locational datasets: Global (all countries), English-speaking countries, Europe, and the United States. However, you can always submit a custom request
The following example illustrates downloading a dataset using a download link and credentials provided by us.
- Download the gzipped JSON file using the provided link and credentials. Click on the file you want to download:
- Unzip the file by clicking on it:
- A JSON file will appear at the unzip location. Each file will have up to 10,000 employee profile records.
The following example illustrates downloading a dataset using a download link and credentials provided by us.
- Click on the link and download the csv.gz file:
- Unzip the file by clicking:
Each gzipped CSV file contains a table with specific data collection (e.g., a job_functions table) from employee profile records.
The gzipped file might contain several files, but they all belong to the same table (e.g., job_functions):
We can only offer general solutions since it depends on the tech stack you use or what you prefer using.
Ingesting a large dataset like Professional Network Jobs can be efficiently managed using a combination of tools and technologies tailored to handle big data workloads.
Tool category | Tool example |
|---|---|
Database systems | |
Data processing frameworks | Apache Spark Apache Hadoop |
Data ingestion tools | Apache NiFi Google BigQuery |
Data ETL (Extract, Transform, Load) tools | |
Data transformation |