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Develop and deploy Lakeflow Jobs on Databricks. Use when creating data engineering jobs with notebooks, Python wheels, or SQL tasks. Invoke BEFORE starting…
Lakeflow Jobs Development
FIRST: Use the parent databricks-core skill for CLI basics, authentication, profile selection, and data exploration commands.
Lakeflow Jobs are scheduled workflows that run notebooks, Python scripts, SQL queries, and other tasks on Databricks.
Scaffolding a New Job Project
Use databricks bundle init with a config file to scaffold non-interactively. This creates a project in the <project_name>/ directory:
databricks bundle init default-python --config-file <(echo '{"project_name": "my_job", "include_job": "yes", "include_pipeline": "no", "include_python": "yes", "serverless": "yes"}') --profile <PROFILE> < /dev/null
project_name: letters, numbers, underscores only
After scaffolding, create CLAUDE.md and AGENTS.md in the project directory. These files are essential to provide agents with guidance on how to work with the project. Use this content:don't have the plugin yet? install it then click "run inline in claude" again.