senior-data-engineer

Quick Review

The skill provides a broad overview of senior data engineering capabilities with good structure and references to supporting files. However, the Description is generic and doesn't clearly specify when/how a CLI agent should invoke this skill versus handle tasks directly. The SKILL.md lists extensive tech stack and patterns but lacks concrete invocation examples tied to specific data engineering scenarios (e.g., 'building Airflow DAG', 'designing dimensional model', 'setting up Kafka streams'). The three scripts appear to be useful tools, but their capabilities aren't clearly mapped to distinct use cases. Task knowledge is moderate - references to external .md files for patterns and best practices are helpful, but the quick start commands are too generic. Novelty is lower because many listed capabilities (SQL, basic ETL, data quality checks) are straightforward for a CLI agent with appropriate prompting, though complex orchestration and performance optimization at scale do add value. To improve: make the Description more specific about invocation triggers, provide clearer mapping between scripts and real-world data engineering tasks, and demonstrate unique value beyond what a well-prompted LLM could achieve.