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Found 26 Skills
Schema Validator - Auto-activating skill for Data Pipelines. Triggers on: schema validator, schema validator Part of the Data Pipelines skill category.
Binary streaming between workers via channels. Use when building data pipelines, file transfers, streaming responses, or any pattern requiring binary data transfer between functions.
Expert guidance for creating, modifying, and optimizing dbt pipelines for BigQuery. Use this skill whenever user asks for generating or modifying a dbt model or project. Activate this skill when the user - Creates, modifies, or troubleshoots **dbt models or pipelines** - Needs to **optimize SQL** within a dbt project - Is **setting up a new dbt project** or configuring existing one
Provides guidance for writing, packaging and executing Apache Beam pipelines on GCP using Cloud Dataflow. Use when: - Creating an Apache Beam Dataflow pipeline. - Creating a Google Flex Template.
Master data engineering, ETL/ELT, data warehousing, SQL optimization, and analytics. Use when building data pipelines, designing data systems, or working with large datasets.
Data Catalog Updater - Auto-activating skill for Data Pipelines. Triggers on: data catalog updater, data catalog updater Part of the Data Pipelines skill category.
Airflow Operator Creator - Auto-activating skill for Data Pipelines. Triggers on: airflow operator creator, airflow operator creator Part of the Data Pipelines skill category.
Master Node.js streams for memory-efficient processing of large datasets, real-time data handling, and building data pipelines
Google Cloud Dataflow integration. Manage data, records, and automate workflows. Use when the user wants to interact with Google Cloud Dataflow data.
Develop Microsoft Fabric Spark/data engineering workflows with intelligent routing to specialized resources. Provides core workspace/lakehouse management and routes to: data engineering patterns, development workflow, or infrastructure orchestration. Use when the user wants to: (1) manage Fabric workspaces and resources, (2) develop notebooks and PySpark applications, (3) design data pipelines and orchestration, (4) provision infrastructure as code. Triggers: "develop notebook", "data engineering", "workspace setup", "pipeline design", "infrastructure provisioning", "Delta Lake patterns", "Spark development", "lakehouse configuration", "organize lakehouse tables", "create Livy session", "notebook deployment".
You are a **Data Engineer**, an expert in designing, building, and operating the data infrastructure that powers analytics, AI, and business intelligence. You turn raw, messy data from diverse sour...
Airbyte integration. Manage data, records, and automate workflows. Use when the user wants to interact with Airbyte data.