Load LinkedIn Jobs API data to DuckDB

LinkedIn's Job Posting API is a partner-facing service that allows approved ATS and distribution partners to create, update, renew, and close job postings on the LinkedIn platform. Everything needed to build a working LinkedIn Jobs API → DuckDB pipeline is on this page: the API's base URL, authentication, endpoints, pagination and incremental field — plus a prompt that hands the whole job to your coding agent.

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Build your LinkedIn Jobs API to DuckDB pipeline

Paste this prompt into Claude, Codex, or Cursor. The agent does the rest.

PromptCopy prompt
Run uvx dlthub-init@latest to build a pipeline from LinkedIn Jobs API to DuckDB and run it on dltHub

That scaffolds a dltHub workspace and installs the dltHub AI harness — the project rules, the secrets-management skill, and the dlt MCP server your agent needs to work safely. From there it reads the LinkedIn Jobs API API, proposes the endpoints to load, then writes, runs and validates the pipeline while you review rather than type. Credentials are inspected through MCP tools, so your agent never reads secrets.toml itself. How the LLM-native workflow works →

Prefer to write it yourself? Every fact the agent uses is below.

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LinkedIn Jobs API API at a glance

These values come from the LinkedIn Jobs API API reference — the authoritative source if anything here looks out of date.

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How do I authenticate with the LinkedIn Jobs API API?

All requests require an Authorization header containing a Bearer token obtained via the OAuth 2.0 Client Credentials flow. Additionally, requests must include a LinkedIn-Version header (formatted as YYYYMM) and sometimes an X-Restli-Method header for specific batch operations.

1. Get your credentials

1. Navigate to the LinkedIn Developer Portal (https://www.linkedin.com/developers/apps). 2. Log in with your LinkedIn account. 3. Click 'Create App' to register a new application, or select an existing one from 'My Apps'. 4. Complete the application details and ensure you have requested the necessary product access (e.g., Job Posting API or other enterprise products). 5. Once the app is created or selected, navigate to the 'Auth' tab. 6. Locate your 'Client ID' (also referred to as your API key or Consumer key) and 'Client Secret'. These credentials will be used to authenticate your API calls. Note: If you are implementing a partner integration requiring individual customer credentials, you must use the Provisioning API to generate API keys for each of your customers.

2. Add them to .dlt/secrets.toml

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[sources.linkedin_jobs_api_source]
linkedin_client_id = "your_client_id_here"
linkedin_client_secret = "your_client_secret_here"

dlt reads this file automatically at runtime. With the harness, the setup-secrets skill prompts you for the values and never handles the raw credential in chat. For production, see setting up credentials with dlt.

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What LinkedIn Jobs API data can I load into DuckDB?

These are the LinkedIn Jobs API endpoints dlt can load into DuckDB:

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How do I load only new LinkedIn Jobs API records?

LinkedIn Jobs API exposes count on rest/simpleJobPostings, so dlt can request only the records that changed since the last run. Set it as the cursor_path and dlt tracks the high-water mark for you between runs.

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{"name": "simple_job_postings", "endpoint": {
    "path": "rest/simpleJobPostings",
    "data_selector": "elements",
    "incremental": {"cursor_path": "count", "initial_value": "2024-01-01T00:00:00Z"},
}}

On the first run dlt loads everything from initial_value; on every run after that it requests only what changed and appends with write_disposition="merge" if you set a primary key. See incremental loading.

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What does the generated LinkedIn Jobs API pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading accessToken and simpleJobPostings from the LinkedIn Jobs API API into DuckDB:

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

@dlt.source
def linkedin_jobs_api_source(client_credentials=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://api.linkedin.com/rest/",
            "auth": {"type": "bearer", "token": client_credentials},
        },
        "resources": [
            {"name": "simple_job_postings", "endpoint": {"path": "rest/simpleJobPostings", "data_selector": "elements"}},
            {"name": "job_posting_tasks", "endpoint": {"path": "rest/simpleJobPostings/{taskId}"}}
        ],
    }
    yield from rest_api_resources(config)


def load_linkedin_jobs_api_to_duckdb() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="linkedin_jobs_api_pipeline",
        destination="duckdb",
        dataset_name="linkedin_jobs_api_data",
    )
    load_info = pipeline.run(linkedin_jobs_api_source())
    print(load_info)


if __name__ == "__main__":
    load_linkedin_jobs_api_to_duckdb()

Run it with python linkedin_jobs_api_pipeline.py. The agent iterates on this until it loads cleanly — you review and approve, rather than write it from scratch.

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How do I query LinkedIn Jobs API data in DuckDB?

dlt creates one table per resource. Query the loaded data with Python or SQL — or ask your agent to, through the MCP server's execute_sql_query tool.

Python (pandas DataFrame):

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import dlt

data = dlt.pipeline("linkedin_jobs_api_pipeline").dataset()
df = data.simple_job_postings.df()
print(df.head())

SQL:

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SELECT * FROM linkedin_jobs_api_data.simple_job_postings LIMIT 10;

See querying your data with dataset and exploring it in marimo notebooks.

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How do I deploy the LinkedIn Jobs API to DuckDB pipeline in production?

The pipeline runs locally, which is ideal for prototyping and one-off analysis. When you need it on a schedule, monitored on every load, and shared with your team, deploy the same dlt code on the dltHub platform — no infrastructure to maintain. The prompt above already ends with "run it on dltHub", so your agent can take it there directly.

• Deploy & schedule — run the pipeline as a managed job with automatic retries.
• Monitor — observable job queues, alerting, and load metrics for every run.
• Transform — promote raw LinkedIn Jobs API loads into governed, documented models.
• Visualize & share — explore data in notebooks and publish live dashboards instead of static screenshots.

Book a demo →

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What other destinations can I load LinkedIn Jobs API data to?

dlt loads into any of these — only the destination argument changes:

Set dlt.pipeline(destination="snowflake") and add credentials in .dlt/secrets.toml. On the dltHub platform the same pipeline runs against a managed Iceberg lakehouse. See the full destinations list.

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Next steps

• Ready for production? Book a demo of the dltHub platform →
• dlt LLM-native workflow docs
• REST API source reference
• Join the dlt community on Slack