aws data analytics — Agent Skill

aws-data-analytics

Overview

This plugin brings AWS data engineering expertise directly into your coding assistant, covering the full data lifecycle across AWS Analytics services; currently, skills are provided to assist with the following capability areas:

• Data Lake Operations — Build and operate a data lake on AWS: create managed Iceberg tables on Amazon S3 Tables, ingest data from diverse sources (S3, JDBC databases, Snowflake, BigQuery, DynamoDB, AWS Glue catalog tables), and query across default and federated catalogs with Amazon Athena.
• Data Discovery — Inventory and audit your AWS Glue Data Catalog across S3 Tables, Amazon Redshift-federated, and remote Iceberg catalogs. Resolve data asset references by name, keyword, column, or reverse-lookup from S3 location metadata in the catalog.
• Data Governance (Amazon SageMaker Catalog) — Curate business metadata in Amazon SageMaker Catalog or the AWS Glue Data Catalog (descriptions, READMEs, glossaries, metadata forms, publishing, and safe asset retirement), and request, approve, share, audit, and revoke access to catalog assets through subscriptions.
• Vector Storage — Store and query vector embeddings using Amazon S3 Vectors for cost-effective semantic search and RAG workloads.
• External Connectivity — Create and troubleshoot AWS Glue connections to JDBC databases (Oracle, SQL Server, PostgreSQL, MySQL, RDS, Aurora), Amazon Redshift, Snowflake, and BigQuery.
• Search & Observability (OpenSearch) — Migrate from Solr/Elasticsearch/self-managed OpenSearch into Amazon OpenSearch Service or Serverless, provision domains and collections, and build vector/semantic/hybrid search, log analytics, and trace analytics.
• Data Warehouse (Amazon Redshift) — Write Redshift SQL on a provisioned cluster or Serverless workgroup: DDL and distribution/sort keys, COPY/UNLOAD, system views, and the Data API.
• Workflow Orchestration (Amazon MWAA) — Author, test, and debug Apache Airflow DAGs on Amazon Managed Workflows for Apache Airflow (MWAA) provisioned environments and YAML workflows on MWAA Serverless, and upgrade provisioned environments to newer Airflow versions, including 2.x to 3.x.
• Streaming (Amazon MSK) — Operate Amazon MSK Provisioned clusters with Standard and Express brokers: size and cost a cluster, troubleshoot performance and consumer lag, manage topics, replicate across clusters with MSK Replicator for disaster recovery and active-active topologies, and deliver topic data to Apache Iceberg tables on S3 Tables with Streaming Tables. Plan and execute a migration from self-managed Apache Kafka to MSK Express.
• Stream Processing (Amazon Managed Service for Apache Flink) — Develop, deploy, and tune Apache Flink applications on Amazon Managed Service for Apache Flink, including checkpointing, state, connectors, dependency management, and Flink 1.x to 2.x migration.

Agent Skills

| # | Skill | Description | Documentation | | -- | -------------------------- | ------------------------------------------------------------------------------------------------------------------------ | ---------------------------------------------------- | | 1 | creating-data-lake-table | Create managed Iceberg tables using Amazon S3 Tables with automatic compaction, AWS Glue catalog registration, and partitioning | SKILL.md | | 2 | ingesting-into-data-lake | Import data from S3 files, JDBC databases, Snowflake, BigQuery, DynamoDB, or existing AWS Glue catalog tables into S3 Tables or standard Iceberg | SKILL.md | | 3 | querying-data-lake | Execute and manage Athena SQL queries across default and federated catalogs (AWS Glue, S3 Tables, Amazon Redshift) | SKILL.md | | 4 | finding-data-lake-assets | Resolve data lake asset references across AWS Glue Data Catalog, S3, S3 Tables, and Amazon Redshift by name, keyword, column, or S3 path | SKILL.md | | 5 | exploring-data-catalog | Full inventory and audit of AWS Glue Data Catalog assets across S3 Tables, Amazon Redshift-federated, and remote Iceberg catalogs | SKILL.md | | 6 | storing-and-querying-vectors | Store and query vector embeddings using Amazon S3 Vectors for semantic search and RAG workloads | SKILL.md | | 7 | connecting-to-data-source | Create and troubleshoot AWS Glue connections to JDBC databases, Amazon Redshift, Snowflake, and BigQuery | SKILL.md | | 8 | amazon-opensearch-service | Migration, provisioning, vector/semantic/hybrid search, log analytics, and trace analytics for Amazon OpenSearch Service and Serverless | SKILL.md | | 9 | redshift-guide | Amazon Redshift SQL dialect, system views, metadata discovery, and Data API patterns, correcting common agent mistakes | SKILL.md | | 10 | authoring-mwaa-workflow | Author and deploy Airflow DAGs for Amazon MWAA provisioned environments and YAML workflows for MWAA Serverless | SKILL.md | | 11 | testing-mwaa-workflow | Trigger a deployed MWAA DAG or Serverless workflow, monitor it to completion, and retest after fixes | SKILL.md | | 12 | debugging-mwaa-workflow | Root-cause failed MWAA runs and tasks, DAGs that don't appear, import errors, worker out-of-memory, and IAM denials | SKILL.md | | 13 | upgrading-mwaa-environments | Upgrade MWAA provisioned environments to a newer Airflow version, including 2.x to 3.x, with a blue/green or in-place strategy | SKILL.md | | 14 | `mana

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