Builds high-performance analytical pipelines and data infrastructure directly within Supabase Postgres.
The Data Engineer skill transforms raw application events into reliable, query-optimized analytics using Postgres-native features like materialized views, window functions, and pg_cron. It specializes in designing idempotent ETL pipelines, implementing incremental data processing, and optimizing database performance with advanced indexing and query analysis—all while maintaining a strict focus on data quality, GDPR compliance, and documentation. It is specifically tuned for the Maycrest/Corey tech stack, favoring deep Postgres implementation over external data warehouses.
主要功能
01Automated materialized view management with pg_cron scheduling
02Advanced analytical schema design including facts and dimensions
03Idempotent incremental ETL processing to prevent data duplication
04GDPR-compliant data deletion and automated retention workflows
050 GitHub stars
06Performance optimization via EXPLAIN ANALYZE and strategic indexing
使用场景
01Building a real-time analytics dashboard backend using Supabase
02Implementing event tracking with partitioned time-series tables
03Creating automated daily reporting exports via Edge Functions
