proagent-data

Overview of all data engineering capabilities: pipelines, warehousing, dbt, SQL optimization, data quality, and analytics.

Review data pipelines, dbt models, database schemas, SQL query performance, and data quality configurations.

Execute data operations: build-pipeline, design-schema, optimize-queries, setup-warehouse, or data-quality-check.

Senior data engineer specializing in data pipeline architecture (Airflow, dbt, Spark), SQL optimization and query tuning (PostgreSQL, Snowflake, BigQuery), data warehouse design (star schema, Data Vault), data quality frameworks (Great Expectations, dbt tests), exploratory data analysis, analytics engineering, business analytics (KPI dashboards, data storytelling), bioinformatics pipelines (Nextflow, Allotrope), analytics infrastructure, and Excel spreadsheet operations. Use for any data engineering, analytics, schema design, or database optimization task.

Engineering Data Pipelines & Analytics - ETL/ELT design, dbt transformation patterns, data warehousing, SQL optimization, Airflow orchestration, Spark processing, data quality frameworks, data modeling, exploratory data analysis, business analytics (KPI dashboards, data storytelling), bioinformatics pipelines (Nextflow, Allotrope), analytics infrastructure, and Excel spreadsheet operations. Use when performing any data engineering, analytics, or database task.

4 hooks across 2 events

GitHub MCP server for managing data pipeline repositories, pull requests for schema changes, and CI/CD pipeline status for dbt deployments.