The following directory acts as an Extract-Transform-Load (ETL) pipeline, transporting and re-structuring raw, unformatted data to Dimension and Fact tables, specifically in accordance with several predetermined, outlined Star Schemas. This is achieved primarily through the use of Cloud Engineering, Data Engineering and Code as Infrastructure principals and thus fundamentally relies on the commissioning of Amazon-Web-Services (AWS) resources utilising Terraform along-side fully tested and reviewed Python scripts. In addition, throughout the project, Continuous Integration and Continuous Delivery (CI/CD) was practiced, alongside Test-Driven Development (TTD) to maximise both the effectiveness and validity of such code, as written and deployed. Principally, the structure of this infrastructure is represented within the above diagram. A scheduler was initialised to trigger an AWS State-Machine every 20 minutes, which in-turn activates all three lambda sequentially encapsulated within the aforementioned State-Machine.