What problem does it solve?
This Skill eliminates the risk of writing non-idiomatic, error-prone Go code for data engineering tasks, extending the base data-engineer role with Go-specific best practices to ensure your pipelines, workers, and services follow Go's core design principles and clean code standards.
Core Features & Use Cases
- Idiomatic Go Implementation: Build ETL pipelines, streaming workers, CLI tools, and high-throughput services using Go-specific patterns including explicit error returns, implicit interface satisfaction, goroutine/channel concurrency, context propagation, and generics (1.18+).
- Clean Code Review: Audit existing Go code for compliance with shared clean code standards and Go language best practices.
- Safe Concurrency Design: Implement bounded, race-safe goroutine and channel patterns including worker pools, fan-in/fan-out, and context propagation for streaming workloads.
- Use Case: If you are building a real-time transaction processing pipeline in Go, this skill ensures you avoid common pitfalls like unbounded goroutine leaks, improper error wrapping, and non-idiomatic interface usage.
Quick Start
Use the go-data-engineer skill to implement a bounded-concurrency Go ETL pipeline that processes CSV transaction records, applies business logic transformations, and writes results to a PostgreSQL database with proper error wrapping and race-safe unit tests.
