AAS Data Engineering Platform

Plugin aasb-aas-data-engineering-platform in sickn33/agentic-awesome-skills. Commands read from the repo's manifest — today.

Skills (11)

• airflow-dag-patterns

  Build production Apache Airflow DAGs with best practices for operators, sensors, testing, and deployment. Use when creating data pipelines, orchestrating workflows, or scheduling batch jobs.

• data-engineer

  Build scalable data pipelines, modern data warehouses, and real-time streaming architectures. Implements Apache Spark, dbt, Airflow, and cloud-native data platforms.

• data-quality-frameworks

  Implement data quality validation with Great Expectations, dbt tests, and data contracts. Use when building data quality pipelines, implementing validation rules, or establishing data contracts.

• database-architect

  Expert database architect specializing in data layer design from scratch, technology selection, schema modeling, and scalable database architectures.

• dbt-transformation-patterns

  Production-ready patterns for dbt (data build tool) including model organization, testing strategies, documentation, and incremental processing.

• embedding-strategies

  Guide to selecting and optimizing embedding models for vector search applications.

• postgres-best-practices

  Postgres performance optimization and best practices from Supabase. Use this skill when writing, reviewing, or optimizing Postgres queries, schema designs, or database configurations.

• rag-engineer

  Expert in building Retrieval-Augmented Generation systems. Masters embedding models, vector databases, chunking strategies, and retrieval optimization for LLM applications.

• sql-pro

  Master modern SQL with cloud-native databases, OLTP/OLAP optimization, and advanced query techniques. Expert in performance tuning, data modeling, and hybrid analytical systems.

• vector-database-engineer

  Expert in vector databases, embedding strategies, and semantic search implementation. Masters Pinecone, Weaviate, Qdrant, Milvus, and pgvector for RAG applications, recommendation systems, and similar

• warehouse

  Plan and review read-only data warehouse analysis with explicit scope, privacy, provenance, and validation checks.

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