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databricks-jobs

Manage Databricks Jobs lifecycle with CLI, SDK, and Asset Bundles.

Updated May 20, 2026

Search Tags:#asset bundles #cli automation #job monitoring #job orchestration #scheduled workflows #databricks jobs #run now

Ready to run

npx skills add https://github.com/ice-droid-99/BI-Dashboard-Generation-Agent-in-Databricks- --skill databricks-jobs-ice-droid-99

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: databricks-jobs
Source: https://github.com/ice-droid-99/BI-Dashboard-Generation-Agent-in-Databricks-/tree/main/.gemini/skills/databricks-jobs
Command: npx skills add https://github.com/ice-droid-99/BI-Dashboard-Generation-Agent-in-Databricks- --skill databricks-jobs-ice-droid-99

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill helps you reliably create, inspect, run, update, and delete Databricks Jobs instead of relying on general Databricks guidance, reducing configuration mistakes and speeding up operational workflows.

Core Features & Use Cases

Job lifecycle operations: Create, list, get, run-now, cancel runs, update, and delete Jobs using Databricks Jobs APIs/CLI/SDK/Asset Bundles.
Workflow orchestration support: Define multi-task DAGs with dependencies (including run_if conditions like ALL_SUCCESS/ALL_DONE) and cross-job orchestration via run_job_task.
Production-ready configurations: Configure triggers and schedules (cron/periodic/file arrival/table update/continuous), notifications and health rules, permissions, and common compute setup patterns.

Quick Start

Use the databricks-jobs skill to create a new scheduled multi-task ETL Job for a given workspace path and cron schedule, then return the exact CLI or SDK structure needed to deploy it.

Frequently Asked Questions about databricks-jobs

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I create a scheduled multi-task Databricks Job with DAG dependencies?▼

To create a scheduled multi-task Databricks Job, you define task dependencies using DAG conditions like run_if ALL_SUCCESS or ALL_DONE, then apply the configuration via Databricks Jobs APIs, CLI, SDK, or Asset Bundles to deploy the workflow.

Can I trigger Databricks Jobs on file arrival or table updates?▼

Yes, Databricks Jobs support multiple trigger types including cron schedules, periodic intervals, file arrival, table updates, and continuous execution, allowing you to automate operational data workflows based on your specific event requirements.

What is the best way to manage Databricks Jobs end-to-end using Asset Bundles?▼

Managing Databricks Jobs end-to-end with Asset Bundles involves defining your job structures, tasks, compute configurations, and permissions in bundle files, then deploying them to ensure consistent job lifecycle operations across environments.

How do I configure notifications and health rules for Databricks Jobs?▼

You configure notifications and health rules for Databricks Jobs by defining alert policies within the job configuration JSON or Asset Bundles, specifying conditions for job failures, timeouts, or stream delays to monitor workflow health effectively.

Does Databricks Jobs CLI support cross-job orchestration?▼

Yes, Databricks Jobs CLI supports cross-job orchestration through the run_job_task feature, allowing one job to trigger another and enabling complex multi-workflow dependencies across your operational data pipelines.

Why do my Databricks Jobs fail during common compute configuration setups?▼

Databricks Jobs often fail due to misconfigured compute settings, invalid task parameters, or incorrect JSON structures; this Skill provides guidance on proper compute configuration and common failure modes to prevent operational issues.