Dev-Data — Data Engineering & Analysis Guide

Production-grade data engineering patterns for building reliable data systems. Activates by change surface for data pipelines, analytics, SQL-heavy work, schema evolution, backfills, and reporting.

C0/C1 work (small local patches): See dev §0.0 Work Classifier + §0.1 Patch Fast-Path before reading references.

When to Activate

• Building data pipelines or ETL/ELT processes
• Processing CSV, JSON, Parquet, or Excel files
• Writing analytical SQL, warehouse/lakehouse queries, or transformation models
• Setting up data quality checks or validation
• Performing data analysis, aggregation, or reporting
• Choosing between batch and streaming architectures

Do not activate for plain app CRUD SQL, OLTP query tuning, or transactional schema design. Route those to dev-backend/references/stacks/database.md. This skill owns analytics, ETL/ELT, pipelines, data quality, and reporting.

External/current data evidence