data-engineer
Specialized data engineering agent for designing ETL/ELT pipelines, defining data schemas, managing data quality, and implementing robust ingestion workflows.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
114 skills found
Specialized data engineering agent for designing ETL/ELT pipelines, defining data schemas, managing data quality, and implementing robust ingestion workflows.
Create, manage, and debug dlt (data load tool) pipelines for ingesting data from APIs, databases, and custom sources into destinations like DuckDB, BigQuery, and Snowflake.
Expert SQL agent for modern database systems, query optimization, HTAP environments, and data architecture patterns. Optimize performance, schema design, and analytical workloads effectively.
Expert database design and access patterns: schema architecture, indexing strategies, query optimization, repository patterns, and transaction management for SQL and NoSQL databases.
A multi-paradigm ETL pipeline agent supporting batch and streaming data processing, schema inference, and configurable DAG-based transformations for heterogeneous data sources.
Configure and manage Snowflake connections for CLI, Streamlit, and Snowpark environments, including authentication methods like SSO, key pair, OAuth, and profile management.
Executes SQL queries against the WordPress development database for inspection, troubleshooting, and audit log analysis.
Generate optimized SQL queries from natural language. Supports BigQuery, PostgreSQL, MySQL, and Snowflake. Analyze database schemas, interpret business requirements, and output ready-to-run queries with explanations.
A versatile data analysis assistant for loading datasets, performing statistical calculations, visualizing trends, and generating professional summary reports.
CLI tool to bundle repository context, files, and prompts into a one-shot request for advanced AI debugging, refactoring, and code review.
World-class senior data engineering skill for building scalable data pipelines, ETL/ELT systems, and modern data infrastructure using Python, Spark, dbt, and Kafka.
Integrate Snowflake with MCP clients. Manage Snowflake endpoints, validate connectivity, and leverage Cortex AI (Search, Analyst, Agent) services directly within your AI workflow.