Zenefits Python API Docs | dltHub

Zenefits is a RESTful HR platform API that provides access to company, people (employees), benefits, payroll, platform applications and lifecycle events data. The REST API base URL is https://api.zenefits.com and All requests require OAuth2 Bearer access tokens in the Authorization header..

dlt is an open-source Python library that handles authentication, pagination, and schema evolution automatically. dlthub provides AI context files that enable code assistants to generate production-ready pipelines. Install with uv pip install "dlt[workspace]" and start loading Zenefits data in under 10 minutes.

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What data can I load from Zenefits?

Here are some of the endpoints you can load from Zenefits:

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How do I authenticate with the Zenefits API?

Zenefits uses OAuth2 (admin‑authorized) apps. Developers register an app to get a Client ID and Client Secret, exchange an authorization code for an access token, and include "Authorization: Bearer <access_token>" in each request. Webhooks use a separate shared secret and HMAC‑SHA256 signature header.

1. Get your credentials

1. Create a developer account and register an OAuth application with Zenefits. 2) Record the Client ID and Client Secret provided. 3) Direct an admin user to the Zenefits authorization URL to obtain an authorization code. 4) Exchange the authorization code at the token endpoint to receive an access_token (Bearer). 5) Use the access_token in the Authorization header for API calls. For webhooks, generate a webhook shared secret in the app settings for HMAC‑SHA256 signature verification.

2. Add them to .dlt/secrets.toml

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[sources.zenefits_hr_source]
access_token = "your_access_token_here"

dlt reads this automatically at runtime — never hardcode tokens in your pipeline script. For production environments, see setting up credentials with dlt for environment variable and vault-based options.

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How do I set up and run the pipeline?

Set up a virtual environment and install dlt:

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uv venv && source .venv/bin/activate
uv pip install "dlt[workspace]"

1. Install the dlt AI Workbench:

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dlt ai init --agent <your-agent> # <agent>: claude | cursor | codex

This installs project rules, a secrets management skill, appropriate ignore files, and configures the dlt MCP server for your agent. Learn more →

2. Install the rest-api-pipeline toolkit:

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dlt ai toolkit rest-api-pipeline install

This loads the skills and context about dlt the agent uses to build the pipeline iteratively, efficiently, and safely. The agent uses MCP tools to inspect credentials — it never needs to read your secrets.toml directly. Learn more →

3. Start LLM-assisted coding:

Use /find-source to load data from the Zenefits API into DuckDB.

The rest-api-pipeline toolkit takes over from here — it reads relevant API documentation, presents you with options for which endpoints to load, and follows a structured workflow to scaffold, debug, and validate the pipeline step by step.

4. Run the pipeline:

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python zenefits_hr_pipeline.py

If everything is configured correctly, you'll see output like this:

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Pipeline zenefits_hr_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset zenefits_hr_data
The duckdb destination used duckdb:/zenefits_hr.duckdb location to store data
Load package 1749667187.541553 is LOADED and contains no failed jobs

Inspect your pipeline and data:

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dlt pipeline zenefits_hr_pipeline show

This opens the Pipeline Dashboard where you can verify pipeline state, load metrics, schema (tables, columns, types), and query the loaded data directly.

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Python pipeline example

This example loads people and companies from the Zenefits API into DuckDB. It mirrors the endpoint and data selector configuration from the table above:

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import dlt
from dlt.sources.rest_api import RESTAPIConfig, rest_api_resources

@dlt.source
def zenefits_hr_source(access_token=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://api.zenefits.com",
            "auth": {
                "type": "bearer",
                "token": access_token,
            },
        },
        "resources": [
            {"name": "people", "endpoint": {"path": "core/people"}},
            {"name": "companies", "endpoint": {"path": "core/companies"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="zenefits_hr_pipeline",
        destination="duckdb",
        dataset_name="zenefits_hr_data",
    )
    load_info = pipeline.run(zenefits_hr_source())
    print(load_info)

To add more endpoints, append entries from the resource table to the "resources" list using the same name, path, and data_selector pattern.

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How do I query the loaded data?

Once the pipeline runs, dlt creates one table per resource. You can query with Python or SQL.

Python (pandas DataFrame):

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import dlt

data = dlt.pipeline("zenefits_hr_pipeline").dataset()
sessions_df = data.people.df()
print(sessions_df.head())

SQL (DuckDB example):

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SELECT * FROM zenefits_hr_data.people LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("zenefits_hr_pipeline").dataset()
data.people.df().head()

See how to explore your data in marimo Notebooks and how to query your data in Python with dataset.

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What destinations can I load Zenefits data to?

dlt supports loading into any of these destinations — only the destination parameter changes:

Change the destination in dlt.pipeline(destination="snowflake") and add credentials in .dlt/secrets.toml. See the full destinations list.

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Troubleshooting

Authentication failures

401 responses occur when the access token is missing or expired. Re‑authenticate via the OAuth flow and ensure Authorization: Bearer <token> header is present.

Webhook verification and signature

Webhook requests include a signature HTTP header: HMAC‑SHA256(payload, webhook_shared_secret). Reject events if the signature does not match. The webhook secret is separate from the OAuth client secret.

Rate limits and retries

The API is primarily read‑only (GET). Server errors (5xx) should be retried with exponential backoff. Zenefits will retry webhook deliveries for up to 1 hour if a non‑2xx status is returned. Pagination is handled via starting_after or ending_before query parameters where supported.

Ensure that the API key is valid to avoid 401 Unauthorized errors. Also, verify endpoint paths and parameters to avoid 404 Not Found errors.

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Next steps

Continue your data engineering journey with the other toolkits of the dltHub AI Workbench:

• data-exploration — Build custom notebooks, charts, and dashboards for deeper analysis with marimo notebooks.
• dlthub-runtime — Deploy, schedule, and monitor your pipeline in production.

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dlt ai toolkit data-exploration install
dlt ai toolkit dlthub-runtime install

• How to deploy a pipeline
• How to explore your data in marimo Notebooks
• How to query your data in Python with dataset
• Join the dlt community on Slack