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AndreKurait
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ingesting-into-data-lake

Ingest data from diverse sources into AWS data lake targets.

Updated Jun 18, 2026
Search Tags:#migration#iceberg#glue#ingest#data-lake#jdbc#s3-tables
One-click install
npx skills add https://github.com/AndreKurait/claude-marketplace-test --skill ingesting-into-data-lake-andrekurait
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ingesting-into-data-lake
Source: https://github.com/AndreKurait/claude-marketplace-test/tree/main/skills/specialized-skills/analytics-skills/ingesting-into-data-lake
Command: npx skills add https://github.com/AndreKurait/claude-marketplace-test --skill ingesting-into-data-lake-andrekurait

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Ingest data into the AWS data lake from diverse sources, unifying ingestion workflows and reducing manual integration effort.

Core Features & Use Cases

  • Supports ingestion from S3 files, local uploads, JDBC databases (Oracle, SQL Server, PostgreSQL, MySQL, RDS, Aurora), Amazon Redshift, Snowflake, BigQuery, DynamoDB, and existing Glue catalog tables (migration).
  • Default target is S3 Tables with Iceberg support on general-purpose buckets when S3 Tables is not adopted.
  • Handles one-time loads and recurring pipelines, including catalog migrations and ongoing data synchronization.

Quick Start

Configure a Glue-based ingestion job to pull data from your chosen source and write to your target (S3 Tables or Iceberg), then run a test load.

Frequently Asked Questions about ingesting-into-data-lake

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I ingest data from JDBC databases like Oracle and PostgreSQL into an S3 data lake?▼

To ingest data from JDBC databases like Oracle and PostgreSQL into an S3 data lake, configure a Glue-based ingestion job to pull data from your chosen source and write to S3 Tables. The default target is S3 Tables, supporting both one-time loads and recurring pipelines.

Can I migrate existing Glue catalog tables to S3 Tables or Iceberg?▼

Yes, you can migrate existing Glue catalog tables to S3 Tables or Iceberg. The Skill handles catalog migrations by configuring Glue-based jobs to pull from existing Glue catalog tables and write to S3 Tables, or Iceberg on general-purpose buckets when S3 Tables is not adopted.

What sources are supported for ingesting data into an AWS data lake?▼

Supported sources for ingesting data into an AWS data lake include S3 files, local uploads, JDBC databases (Oracle, SQL Server, PostgreSQL, MySQL, RDS, Aurora), Amazon Redshift, Snowflake, BigQuery, DynamoDB, and existing Glue catalog tables for migration workflows.

Do I need AWS Glue to ingest data into S3 Tables?▼

Yes, you need AWS Glue to ingest data into S3 Tables. The Skill requires Glue-based jobs and proper catalog configuration to support both ingestion and migration workflows, unifying the process of pulling data from diverse sources and writing to your target.

When should I use Iceberg instead of S3 Tables for data lake ingestion?▼

You should use Iceberg instead of S3 Tables for data lake ingestion when S3 Tables is not adopted. Iceberg is supported on general-purpose buckets, providing an alternative target format for Glue-based ingestion jobs when the default S3 Tables option is unavailable.

What is the best way to set up recurring data synchronization into an AWS data lake?▼

The best way to set up recurring data synchronization into an AWS data lake is configuring a Glue-based ingestion job to pull data from your chosen source and write to S3 Tables. The Skill handles ongoing data synchronization pipelines alongside one-time loads.

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