database-data-engineer

What problem does it solve? Designing databases and data pipelines without a disciplined approach leads to slow queries, fragile migrations, data loss, and ungoverned analytics. This Skill provides a structured engineering workflow for data modeling, storage selection, query optimization, and pipeline reliability. ## Core Features & Use Cases - Schema and Data Modeling: Design constraints, indexes, transaction boundaries, and safe migrations with rollback strategies for PostgreSQL, MySQL, MongoDB, and Redis. - Query and Performance Optimization: Analyze query plans, benchmark representative workloads, and apply indexing, partitioning, and caching patterns based on measurement. - Data Pipelines and Governance: Build idempotent ETL/ELT ingestion with failure recovery, data quality checks, lineage, and warehouse or lakehouse modeling. - Use Case: When designing a new application's data layer, use this Skill to choose the right storage technology, produce the schema and migrations, and document a backup and disaster-recovery plan. ## Quick Start Ask the assistant to design a PostgreSQL schema with indexes, migrations, and a backup plan for your application's core entities.