data-testing

More from dtsong/data-engineering-skills

• data-observability

  Use this skill when implementing monitoring, alerting, and incident response for data pipelines. Covers freshness monitoring, volume anomaly detection, schema change detection, alerting patterns, and incident response workflows. Common phrases: \"data freshness\", \"pipeline monitoring\", \"data anomaly\", \"schema drift\", \"data alerting\", \"incident response\", \"data observability\", \"stale data\". Do NOT use for writing dbt models (use dbt-transforms), pipeline scheduling (use data-pipelines), or data quality testing as deliverables (use data-testing).

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• duckdb

  Use this skill when working with DuckDB for local data analysis, file ingestion, or data exploration. Covers reading CSV/Excel/Parquet/JSON files into DuckDB, SQL analytics on local data, data profiling, cleaning transformations, and export to various formats. Common phrases: \"analyze this CSV\", \"DuckDB query\", \"local data analysis\", \"read Excel in SQL\", \"profile this data\". Do NOT use for dbt model building (use dbt-transforms with DuckDB adapter) or cloud warehouse administration.

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• data-governance

  Use this skill when implementing data governance as part of engineering work. Covers data cataloging (dbt docs, external tools), lineage documentation, data classification (PII/PHI taxonomy), access control patterns (RBAC, row-level security), and compliance frameworks (GDPR, HIPAA, SOX, CCPA). Common phrases: \"data catalog\", \"data lineage\", \"PII classification\", \"access control\", \"RBAC\", \"data governance\", \"compliance requirements\". Do NOT use for writing dbt models (use dbt-transforms), pipeline orchestration (use data-pipelines), or data quality testing (use data-testing).

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• data-integration

  Use this skill when designing data integrations or connecting systems. Covers iPaaS platforms (Workato, MuleSoft, Boomi), dlt pipelines, API patterns, CDC, webhooks, and Reverse ETL. Common phrases: \"connect these systems\", \"build a dlt pipeline\", \"event-driven architecture\", \"change data capture\". Do NOT use for stream processing frameworks (use event-streaming) or pipeline scheduling (use data-pipelines).

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• python-data-engineering

  Use this skill when writing Python code for data pipelines or transformations. Covers Polars, Pandas, PySpark DataFrames, dbt Python models, API extraction scripts, and data validation with Pydantic or Pandera. Common phrases: \"Polars vs Pandas\", \"PySpark DataFrame\", \"validate this data\", \"Python extraction script\". Do NOT use for SQL-based dbt models (use dbt-transforms) or integration architecture (use data-integration).

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• ai-data-integration

  Use this skill when connecting AI or LLMs to data platforms. Covers MCP servers for warehouses, natural-language-to-SQL, embeddings for data discovery, LLM-powered enrichment, and AI agent data access patterns. Common phrases: \"text-to-SQL\", \"MCP server for Snowflake\", \"LLM data enrichment\", \"AI agent access\". Do NOT use for general data integration (use data-integration) or dbt modeling (use dbt-transforms).

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