ClaudeSuperPower

databricks-jobs

Skill

Develop and deploy Lakeflow Jobs on Databricks via DABs, Python SDK, or the CLI. Use when creating data engineering jobs with notebooks, Python wheels, SQL, dbt, or pipelines. Invoke BEFORE starting implementation.

Install

git clone https://github.com/databricks/databricks-agent-skills.git ~/.claude/skills/databricks-jobs

What is databricks-jobs?

Develop and deploy Lakeflow Jobs on Databricks via DABs, Python SDK, or the CLI. Use when creating data engineering jobs with notebooks, Python wheels, SQL, dbt, or pipelines. Invoke BEFORE starting implementation.

What this can do

Capabilities declared in this component's own frontmatter — not inferred.

Inherit all session tools

Declares no tool restrictions — inherits every session tool

~54 tokens of context used while enabled, before you invoke anything

Documentation

README · ~6 min read

Lakeflow Jobs Development

FIRST: Use the parent databricks-core skill for CLI basics, authentication, profile selection, and data exploration commands.

Lakeflow Jobs orchestrate data workflows with multi-task DAGs, flexible triggers, and comprehensive monitoring. Jobs support diverse task types and can be managed via Asset Bundles (DABs), Python SDK, or CLI.

Reference Files

Use CaseReference File
Configure task types (notebook, Python, SQL, dbt, pipeline, JAR, run_job, for_each)references/task-types.md
Set up triggers and schedules (cron, periodic, file arrival, table update, continuous)references/triggers-schedules.md
Configure notifications, health rules, retries, timeouts, queuesreferences/notifications-monitoring.md
Complete worked examples (ETL, warehouse refresh, event-driven, ML training, multi-env, streaming, cross-job)references/examples.md

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