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Found 35 Skills
Databricks CLI operations: auth, profiles, Unity Catalog, data exploration, jobs, pipelines, clusters, model serving, bundles and more. Contains up-to-date guidelines for all Databricks CLI tasks, useful for all Databricks-related tasks.
Configure Databricks CI/CD integration with GitHub Actions and Asset Bundles. Use when setting up automated testing, configuring CI pipelines, or integrating Databricks deployments into your build process. Trigger with phrases like "databricks CI", "databricks GitHub Actions", "databricks automated tests", "CI databricks", "databricks pipeline".
Build apps on Databricks Apps platform. Use when asked to create dashboards, data apps, analytics tools, or visualizations. Invoke BEFORE starting implementation.
Expert-level Databricks platform, Apache Spark, Delta Lake, MLflow, notebooks, and cluster management
Develop and deploy Lakeflow Jobs on Databricks. Use when creating data engineering jobs with notebooks, Python wheels, or SQL tasks. Invoke BEFORE starting implementation.
Manage Lakebase Postgres Autoscaling projects, branches, and endpoints via Databricks CLI. Use when asked to create, configure, or manage Lakebase Postgres databases, projects, branches, computes, or endpoints.
Build full-stack Databricks applications using APX framework (FastAPI + React).
Create and configure Databricks Asset Bundles (DABs) with best practices for multi-environment deployments. Use when working with: (1) Creating new DAB projects, (2) Adding resources (dashboards, pipelines, jobs, alerts), (3) Configuring multi-environment deployments, (4) Setting up permissions, (5) Deploying or running bundle resources
GitHub Actions and CI/CD patterns for Databricks, including automated testing, deployment, and quality gates.
Databricks development guidance including Python SDK, Databricks Connect, CLI, and REST API. Use when working with databricks-sdk, databricks-connect, or Databricks APIs.
Use this skill proactively for ANY Databricks Jobs task - creating, listing, running, updating, or deleting jobs. Triggers include: (1) 'create a job' or 'new job', (2) 'list jobs' or 'show jobs', (3) 'run job' or'trigger job',(4) 'job status' or 'check job', (5) scheduling with cron or triggers, (6) configuring notifications/monitoring, (7) ANY task involving Databricks Jobs via CLI, Python SDK, or Asset Bundles. ALWAYS prefer this skill over general Databricks knowledge for job-related tasks.
Creates, configures, and updates Databricks Lakeflow Spark Declarative Pipelines (SDP/LDP) using serverless compute. Handles streaming tables, materialized views, CDC, SCD Type 2, and Auto Loader ingestion patterns. Use when building data pipelines, working with Delta Live Tables, ingesting streaming data, implementing change data capture, or when the user mentions SDP, LDP, DLT, Lakeflow pipelines, streaming tables, or bronze/silver/gold medallion architectures.