AWS-Snowflake ELT Setup Support

I’ve already mapped out the overall ELT approach but now need a hands-on specialist to stand up the actual configuration that links my AWS stack to Snowflake and dbt.

Here’s the situation
• Source data sits in Amazon RDS and a few application buckets.
• Raw files will land in S3, then flow through Glue jobs (Python) or DMS for change-data-capture.
• Snowpipe and dbt models will take over inside Snowflake, with Airflow orchestrating everything.

What I need from you
I want the entire pipeline configured, secured, and proven end-to-end. That means creating the right IAM roles and policies, wiring up Glue/DMS to S3, setting up Snowpipe auto-ingest, and making sure dbt models execute under Airflow without manual intervention. Your experience with CDC, role-based access controls, and cost-efficient storage tiers will be critical.

Key deliverables
• Working AWS → Snowflake ingest path (S3, Glue or DMS, Snowpipe)
• Parameterised dbt project deployed to my repo and scheduled via Airflow
• IAM policies and Snowflake roles documented and applied
• Step-by-step runbook so I can reproduce or extend the setup

I’ll provide account access, sample data, and an architectural diagram on day one. Once the pipeline loads a sample table accurately and can be re-run from scratch via Airflow, I’ll consider the engagement complete and release final sign-off.