# Data Dictionary: Multi-source Jobs API
Find all data fields with explanations available in the Multi-source Jobs Data.
Each category includes a table listing the available data fields, their explanations, and data types.
{% tabs %}
{% tab title="Data fields per category" %}
1. [Metadata](#metadata)
2. [Job sources](#job-sources)
3. [Job information](#job-information)
4. [Recruiter information](#recruiter-information)
5. [Location information](#location-information)
6. [Company information](#company-information)
7. [Company funding](#company-funding)
8. [Company technologies](#company-technologies)
9. [Salary information](#salary-information)
10. [Benefits](#benefits)
{% endtab %}
{% endtabs %}
{% hint style="info" %}
All personal/company information mentioned within this context is entirely fictional and is solely intended for illustrative purposes.
{% endhint %}
## Metadata
| Data field | Description | Data type |
| ------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------- |
| `id` | Unified job identifier across all sources | Long |
| job\_id\_expired
| Indicates whether the job cluster is now considered fully expired, with all related jobs deleted and expired. Responses are:
1 – expired. Field value will never change to 0 again;
0 – not expired
| Integer |
| `created_at` | Timestamp when the job record was first created | Timestamp |
| `updated_at` | Timestamp when the job record was last updated | Timestamp |
| `date_posted` | Posting date | Timestamp |
| `valid_through` | Expiry date | Timestamp |
| `status` | Job cluster status after aggregation:
1 – active,2 – expired/inactive,3 – deleted
| Integer |
**Refer to the table example from the data:**
{% code title="Metadata" %}
```json
"id": 12345678,
"job_id_expired": 1,
"created_at": "2025-06-02T00:06:00.000",
"updated_at": "2025-07-22T03:54:10.504",
"date_posted": null,
"valid_through": null,
"status": 3,
```
{% endcode %}
## Job sources
| Data field | Description | Data type |
| ------------- | ------------------------------------------------------------------------------------------------------------------------ | ---------------- |
| `job_sources` | List of job postings from different sources for the same job | Array of structs |
| `source_id` | Source-specific job ID | String |
| `source` | Name of the data source (Professional network, Indeed, Glassdoor, etc.) | String |
| `updated_at` | Last update timestamp from this source | Timestamp |
| `url` | URL of the job post in the source | String |
| `status` | Posting status:
| String |
**Refer to the table example from the data:**
{% code title="Job sources" %}
```json
"job_sources": [
{
"source_id": "1234567890",
"source": "professional network",
"updated_at": "2025-07-01T05:53:10.535",
"url": "https://www.professional-network.com/jobs/service-specialist-1234567890",
"status": "deleted"
},
{
"source_id": "indeed_job_1a2b3c4d",
"source": "indeed",
"updated_at": "2025-07-10T00:21:00.000",
"url": "https://www.indeed.com/view-job?jk=1a2b3c4d",
"status": "inactive"
},
{
"source_id": "glassdoor_job_1020304050",
"source": "glassdoor",
"updated_at": "2025-07-22T03:54:10.504",
"url": "https://www.glassdoor.com/job-listing/service-specialist-?ab=1020304050",
"status": "inactive"
}
],
```
{% endcode %}
## Job information
| Data field | Description | Data type |
| ------------------------ | ------------------------------------------------------------------------------------------------------------------------------- | ---------------- |
| `title` | Standardized job title | String |
| `description` | Cleaned full description | String |
| `department` | Department name | String |
| `management_level` | Management responsibility level | String |
| `is_decision_maker` | Marks if the employee is a decision maker, based on `active_experience_title` | Boolean |
| `seniority` | Level of seniority | String |
| `functions` | Standardized job functions | Array of strings |
| `external_url` | External (company) job URL | String |
| `applicants_count` | Number of applicants | String |
| `employment_type` | Standardised values to display one of the values: “Full-time “, “Part-time“, “Contract”, “Temporary“, “Internship“, “Volunteer“ | String |
| `shift_schedule` | List of shift types (e.g., “Monday – Friday”) | Array of strings |
| `accepts_remote` | Accepts remote work | Boolean |
| `is_urgently_hiring` | Urgent hire | Boolean |
| `is_easy_apply` | Supports “quick apply” | Boolean |
| `is_responsive_employer` | Employer marked as responsive | Boolean |
**Refer to the table example from the data:**
{% code title="Job information" %}
```json
"title": "Backend Engineer",
"description": "We're looking for a skilled backend engineer to join our growing team.",
"department": "Engineering and Technical",
"management_level": "Specialist",
"is_decision_maker": false,
"seniority": "Mid-Senior level",
"functions": [
"Backend Engineer"
],
"external_url": null,
"applicants_count": "Be among the first 25 applicants",
"employment_type": "Full-time",
"is_urgently_hiring": false,
"is_easy_apply": false,
"is_responsive_employer": false,
"shift_schedule": [
"Monday to Friday"
],
"accepts_remote": false,
```
{% endcode %}
## Recruiter information
| Data field | Description | Data type |
| ------------- | --------------------------------------- | --------- |
| `recruiter` | Recruiter or contact data, if available | Struct |
| `profile_url` | Recruiter’s public profile URL | String |
| `full_name` | Full name | String |
| `first_name` | First name | String |
| `middle_name` | Middle name | String |
| `last_name` | Last name | String |
**Refer to the table example from the data:**
{% code title="Recruiter information" %}
```json
"recruiter": {
"profile_url": "https://www.professional-network.com/john-doe",
"full_name": "John Doe",
"first_name": "John",
"middle_name": null,
"last_name": "Doe"
},
```
{% endcode %}
## Location information
| Data field | Description | Data type |
| ----------- | ------------------------------------ | --------- |
| `location` | Job location | String |
| `country` | Country | String |
| `city` | City | String |
| `state` | State | String |
| `latitude` | Latitude of location (if available) | Float |
| `longitude` | Longitude of location (if available) | Float |
**Refer to the table example from the data:**
{% code title="Location information" %}
```json
"location": "Akron, OH",
"country": "United States",
"city": "Akron",
"state": "Ohio",
"latitude": 41.0812,
"longitude": 81.5188,
```
{% endcode %}
## Company information
| Data field | Description | Data type |
| --------------------------------- | ------------------------------------------------------------------------------------------------------ | ---------------- |
| `company_ids` | Source-specific company IDs | Struct |
| `professional_network_company_id` | Professional network company ID | Long |
| `gd_company_id` | Glassdoor company ID | String |
| `ind_company_id` | Indeed company ID | String |
| `company_name` | Standardized company name | String |
| `company_url` | Company's website | String |
| `company_domain` | Cleaned the main company domain | String |
| `company_logo_url` | Logo URL (available from Professional network only) | String |
| `company_description` | Short description | String |
| `company_size_range` | Company size based on employee count range (as selected by the company profile administrator) | String |
| `company_employees_count` | Number of employees on Professional network who associated their experience with the company | Long |
| `company_followers` | Company's profile follower count on Professional network | Integer |
| `company_industry` | Primary industry | String |
| `company_type` | Company type | String |
| `company_enriched_keywords` | Categories and keywords that are assigned to the company profile and products across various platforms | Array of strings |
| `company_hq_region` | Detailed region where the company's headquarters is located | Array of strings |
| `company_hq_country` | Country where the company's headquarters is located | String |
| `company_hq_country_iso2` | ISO 2-letter code of the headquarters country | String |
| `company_hq_country_iso3` | ISO 3-letter code of the headquarters country | String |
| `company_hq_location` | Headquarters location | String |
| `company_hq_full_address` | Full address of the headquarters | String |
| `company_hq_city` | Headquarters city | String |
| `company_hq_state` | Headquarters state | String |
| `company_hq_street` | Headquarters street address | String |
| `company_hq_zipcode` | Headquarters zip code | String |
| `company_locations_full` | List of company locations | Array of structs |
| `location_address` | Company location address | String |
| `is_primary` | Indicates if this is the primary company location | Integer |
**Refer to the table example from the data:**
{% code title="Company information" %}
```json
"company_ids": {
"professional_network_company_id": 10779556,
"gd_company_id": null,
"ind_company_id": "Example-Company-1"
},
"company_name": "Example Company",
"company_url": "http://www.example-company.com",
"company_domain": "example-company.com",
"company_logo_url": "https://www.professional-network.com/logo.png",
"company_description": "Example Company provides innovative software solutions for businesses.",
"company_size_range": "501-1000 employees",
"company_employees_count": 1000,
"company_followers": 12345,
"company_industry": "Software",
"company_type": "Private",
"company_enriched_keywords": [
"AI",
"Cloud",
"SaaS",
"Business Tools"
],
"company_hq_region": [
"Americas",
"Northern America",
"AMER"
],
"company_hq_country": "United States",
"company_hq_country_iso2": "US",
"company_hq_country_iso3": "USA",
"company_hq_location": "Austin, TX, United States",
"company_hq_full_address": "123 Main Street; Suite 500; Austin, TX 78701, US",
"company_hq_city": "Austin",
"company_hq_state": "Texas",
"company_hq_street": "123 Main Street; Suite 500",
"company_hq_zipcode": "78701",
"company_locations_full": [
{
"location_address": "123 Main St, Cityville, USA",
"is_primary": true
}
],
```
{% endcode %}
## Company funding
| Data field | Description | Data type |
| --------------------------------------------------- | -------------------------------------- | ---------------- |
| `company_last_funding_round_name` | Last funding round (e.g., Series A) | String |
| `company_last_funding_round_announced_date` | Date of the latest funding round | Date |
| `company_last_funding_round_lead_investors` | Lead investors | Array of strings |
| `company_last_funding_round_amount_raised` | Amount raised in the most recent round | Long |
| `company_last_funding_round_amount_raised_currency` | Currency of the raised amount | String |
| `company_last_funding_round_num_investors` | Number of investors | Long |
**Refer to the table example from the data:**
{% code title="Company funding" %}
```json
"company_last_funding_round_name": "Example funding round name",
"company_last_funding_round_announced_date": "2025-08-20",
"company_last_funding_round_lead_investors": [
"John Doe"
],
"company_last_funding_round_amount_raised": 10000000,
"company_last_funding_round_amount_raised_currency": "USD",
"company_last_funding_round_num_investors": 1,
```
{% endcode %}
## Company technologies
| Data field | Description | Data type |
| --------------------------- | ---------------------------------- | ---------------- |
| `company_technologies_used` | Technologies used by the company | Array of structs |
| `technology` | Technology name | String |
| `first_verified_at` | When was technology first verified | Date |
| `last_verified_at` | When was technology last verified | Date |
**Refer to the table example from the data:**
{% code title="Company technologies" %}
```json
"company_technologies": [
{
"technology": "figma",
"first_verified_at": "2023-06-01",
"last_verified_at": "2025-07-09"
},
{
"technology": "microsoft",
"first_verified_at": "2025-06-20",
"last_verified_at": "2025-08-04"
}
]
```
{% endcode %}
## Salary information
| Data field | Description | Data type |
| ----------- | ------------------------------------------------------------------- | ---------------- |
| `salary` | All salary records for this job | Array of structs |
| `min_value` | Minimum advertised salary | Float |
| `max_value` | Maximum advertised salary | Float |
| `currency` | Salary currency | String |
| `type` | One of the following values: "Year", "Month", "Week", "Day", "Hour" | String |
| `text` | Raw/cleaned salary text | String |
| `source` | Source name | String |
**Refer to the table example from the data:**
{% code title="Salary information" %}
```json
"salary": [
{
"min_value": 28.33,
"max_value": 43.11,
"currency": "USD",
"type": "HOUR",
"text": "$28.33 - $43.11 an hour",
"source": "indeed"
}
]
```
{% endcode %}
## Benefits
| Data field | Description | Data type |
| ---------- | --------------------------------------------------- | ---------------- |
| `benefits` | List of job benefits ("healthcare", "remote", etc.) | Array of strings |
**Refer to the table example from the data:**
{% code title="Benefits" %}
```json
"benefits": [
"employee discount",
"life insurance",
"paid sick time",
"vision insurance",
"dental insurance",
"health savings account",
"health insurance"
]
```
{% endcode %}