A Job in Polysync is a template for a unit of work that can be executed on a connected Platform — for example a single Azure Data Factory pipeline, a Databricks notebook, an Azure Function, or a Google Cloud Function. A Job captures:
Jobs do not run on their own. To execute a job you create one or more Tasks from it. Each Task pins concrete parameter values, schedules, dependencies, retry behaviour, and contention profiles.
| Tab | What you configure |
|---|---|
| General | Job name, Platform (locked after save), Job Type, Platform Job picker (pre-fills settings from the platform artefact), External Id. |
| Parameters | The parameter schema — names, data types, and default values that Tasks will inherit. |
| Settings | Job-level attribute values (e.g., connection or execution settings specific to the job type). |
list_platform_pipelines →
import_platform_jobs.Open a Job in the editor (or ask the AI Copilot via configure_job) to
update its display name, description, parameter defaults, or any other
attribute. Use the Sync Parameters button to re-fetch the parameter
list and settings from the platform after the artefact has changed —
this keeps the schema in sync without recreating the Job.
Use the Create Task button in the Job editor (or the AI Copilot's
create_task_from_job tool) to spin up a Task. You provide a Task name
and the Task starts as a fresh instance of the Job's parameters; you then
override values, add a schedule, and link contention profiles.
The Execute Now button runs the job directly on the Platform without creating a persistent Task. A parameter-override dialog lets you change any value for that single execution. Use this to:
Execution is monitored live in the editor — the button changes to a spinning Running indicator while the job is active.
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