Get employee data from Rippling API

Introduction

Rippling’s API gives teams a straightforward way to automate employee data retrieval across HR, IT, and payroll workflows. This guide walks through exactly how to pull employee records, for a single user or your entire workforce, using Rippling’s API.

It’s part of our deep-dive series on Rippling APi integrations, where we break down authentication, rate limits, and real-world implementation patterns. If you want the full ecosystem view, you can explore the complete guide on the Rippling API here.

Getting Employee Data from the Rippling API

Prerequisites

• A valid Rippling API key or access token
• Python environment with requests installed
• Basic familiarity with REST APIs

Key API Endpoints

• Single employee: https://api.rippling.com/platform/api/employees/{employeeId}
• All employees: https://api.rippling.com/platform/api/employees

Step-by-Step Guide

1. Retrieve Data for One Employee

import requests

def get_single_employee(employee_id, token):
    url = f"https://api.rippling.com/platform/api/employees/{employee_id}"
    headers = {
        "Authorization": f"Bearer {token}",
        "Accept": "application/json"
    }
    response = requests.get(url, headers=headers)
    return response.json()

# Example usage
employee_data = get_single_employee("employeeId", "your_access_token")
print(employee_data)

2. Retrieve Data for All Employees

import requests

def get_all_employees(token, limit=100, offset=0):
    url = "https://api.rippling.com/platform/api/employees"
    headers = {
        "Authorization": f"Bearer {token}",
        "Accept": "application/json"
    }
    params = {
        "limit": limit,
        "offset": offset
    }
    response = requests.get(url, headers=headers, params=params)
    return response.json()

# Example usage
all_employees_data = get_all_employees("your_access_token")
print(all_employees_data)

Common Pitfalls to Avoid

1. Skipping pagination — large datasets will silently truncate without limit/offset handling.
2. Using the wrong endpoints — Rippling has multiple employee-related routes; pick the right one for your use case.
3. Invalid or expired tokens — most 401s come from token mismanagement.
4. Not planning for rate limits — bulk syncs require throttling.
5. Ignoring error codes — Rippling provides helpful error messaging; surface it in your logs.
6. Assuming fields are consistent — optional attributes vary widely across employees.
7. Not validating nulls — missing or blank values will break naïve JSON processing.

Frequently Asked Questions

1. What’s the maximum pagination limit?
Up to 100 records per request.

2. How do I authenticate with the Rippling API?
Use a bearer token in the Authorization header.

3. Can I pull terminated employees?
Yes, use the include_terminated parameter when fetching employee lists.

4. Are all fields guaranteed?
Only core identifiers like id, personalEmail, and roleState are consistently present.

5. Can these endpoints update employee data?
No. They’re read-only.

6. Can I filter employees (e.g., by department)?
Filtering isn’t natively supported in the API; apply filters client-side after retrieval.

7. How should I handle API errors?
Always check status codes, log error bodies, and implement retries/backoff for transient failures.

Knit: A Simpler Way to Work with the Rippling API

If you’d rather not build and maintain your own Rippling API integration, Knit gives you a unified layer to pull employee data with a single connection. Knit handles authentication, token refresh, version changes, and schema reconciliation, removing the operational overhead of managing the integration yourself.

For teams that want to ship fast without babysitting APIs, this becomes the cleaner, more scalable option.

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