Create a pipeline step that uploads data to S3

[mark-torres10]

Issue Description

Epic link: #53

Add a new step, in data_platform, called data_platform/s3_sync/, that takes the dataset ID and syncs all the raw posts, the preprocessed posts, the features, and the curated data, and uploads to S3. Let's use a bucket "lab_data_integrations_interface" (will need Terraform to define this bucket). Let's use the s3 prefix data/{integration}/{dataset ID}/{raw/preprocessed/features/curated}/ matching what we see locally.

Some things to consider:

• Should we upload all data to S3? Or just newly added ones?
• What if a file has been changed since it was uploaded to S3? Should we re-upload it?

[coderabbitai]

⚠️ Possible Duplicate Issue(s)

• [Epic] Implement data ingestion pipeline #53

---

📝 Issue Planner

_{Check the box below or use the @coderabbitai plan command to generate an implementation plan and prompts that you can use with your favorite coding assistant.}

• Create Plan

---

🧪 Issue enrichment is currently in open beta.

You can configure auto-planning by selecting labels in the issue_enrichment configuration.

To disable automatic issue enrichment, add the following to your .coderabbit.yaml:

issue_enrichment:
  auto_enrich:
    enabled: false

💬 Have feedback or questions? Drop into our discord!