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.
---
name: databricks-jobs
description: 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.
compatibility: Requires databricks CLI (>= v1.0.0)
metadata:
version: "0.2.0"
parent: databricks-core
---
# 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 Case | Reference File |
|----------|----------------|
| Configure task types (notebook, Python, SQL, dbt, pipeline, JAR, run_job, for_each) | [references/task-types.md](references/task-types.md) |
| Set up triggers and schedules (cron, periodic, file arrival, table update, continuous) | [references/triggers-schedules.md](references/triggers-schedules.md) |
| Configure notifications, health rules, retries, timeouts, queues | [references/notifications-monitoring.md](references/notifications-monitoring.md) |
| Complete worked examples (ETL, warehouse refresh, event-driven, ML training, multi-env, streaming, cross-job) | [references/examples.md](references/examples.md) |
## Scaffolding a New Job Project… install to load the full skill