ai-data-integration

More from dtsong/data-engineering-skills

• 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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• dlt-extract

  Use this skill when building DLT pipelines for file-based or consulting data extraction. Covers Excel/CSV/SharePoint ingestion via DLT, destination swapping (DuckDB dev to warehouse prod), schema contracts for cleaning, and portable pipeline patterns. Common phrases: \"dlt pipeline for files\", \"extract Excel with dlt\", \"portable data pipeline\", \"dlt filesystem source\". Do NOT use for core DLT concepts like REST API or SQL database sources (use data-integration) or pipeline scheduling (use data-pipelines).

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• data-testing

  Use this skill when designing testing strategies for data pipelines, writing SQL assertions, validating pipeline output, or packaging tests as client deliverables. Covers dbt test patterns, pipeline validation, SQL assertion libraries, test coverage targets, and test-as-deliverable packaging. Common phrases: \"data testing strategy\", \"pipeline validation\", \"SQL assertions\", \"test coverage\", \"test as deliverable\", \"data quality tests\". Do NOT use for writing dbt models (use dbt-transforms), DuckDB analytical queries (use duckdb), or pipeline scheduling (use data-pipelines).

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• data-pipelines

  Use this skill when scheduling, orchestrating, or monitoring data pipelines. Covers Dagster assets, Airflow DAGs, Prefect flows, sensors, retries, alerting, and cross-tool integrations (dagster-dbt, dagster-dlt). Common phrases: \"schedule this pipeline\", \"Dagster vs Airflow\", \"add retry logic\", \"pipeline alerting\", \"consulting pipeline\". Do NOT use for building transformations (use dbt-transforms or python-data-engineering) or designing integration patterns (use data-integration).

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• dbt-transforms

  Use this skill when building or reviewing dbt models, tests, or project structure. Triggers on analytics engineering tasks including staging/marts layers, materializations, incremental strategies, Jinja macros, sources, warehouse configuration, DuckDB adapter, data cleaning, and deduplication patterns. Common phrases: \"dbt model\", \"write a dbt test\", \"incremental strategy\", \"semantic layer\", \"dbt DuckDB\", \"cleaning patterns\". Do NOT use for Python DataFrame code (use python-data-engineering), pipeline scheduling (use data-pipelines), or standalone DuckDB queries without dbt (use duckdb).

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• tsfm-forecast

  Use this skill when generating time-series forecasting pipelines using foundation models. Covers TimesFM, Chronos, MOIRAI, and Lag-Llama model selection, DuckDB-based preprocessing code, Python inference generation, backtesting harnesses, multi-model comparison, and client forecast deliverables. Common phrases: \"time-series forecast\", \"demand forecasting\", \"TimesFM\", \"Chronos\", \"predict future values\", \"zero-shot forecast\". Do NOT use for ML model training or fine-tuning (use python-data-engineering), real-time/streaming forecasts (use event-streaming), or pipeline scheduling (use data-pipelines).

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