What problem does it solve? Manually creating and configuring AWS infrastructure for data pipelines is error-prone, hard to reproduce, and difficult to track. This Skill provides Infrastructure-as-Code patterns with Terraform so data engineering environments can be provisioned, versioned, and torn down consistently. ## Core Features & Use Cases - AWS Resource Provisioning: Create S3 buckets with versioning and lifecycle rules, EC2 instances for data processing, and IAM roles with least-privilege access policies. - State & Environment Management: Use Terraform state commands, workspaces, variable files, and remote S3 backends with DynamoDB locking for multi-environment setups. - Troubleshooting Guidance: Resolve common issues like state locks, credential errors, and resource conflicts with concrete CLI commands. - Use Case: A data engineer needs a reproducible dev environment with a data lake bucket and a processing server. They run terraform plan and apply with the provided HCL configurations, then verify resources with AWS CLI commands. ## Quick Start Ask the AI to generate a Terraform configuration that provisions an S3 data lake bucket and an EC2 instance for data processing in us-east-1.