Ingesting data from multiple external vastly different sources at hundreds of rich data points per second, moving terabytes of data while processing it in real-time, running complex and complicated prediction and forecasting AI models while coupling their output into a hybrid human‑machine data refinement process and presenting the result through a nimble low‑latency SaaS solution used by customers around the globe is no small feat of science and engineering. This processing requires a highly reliable, stable, fault‑tolerant infrastructure that can withstand multiple and varied uses and abuses by data analysts, data scientists, industry experts, and the end‑users. Fast product iteration cycles necessitate a platform that allows engineers to deploy frequently, independently, and without in-depth knowledge of infrastructure complexities.

The Data Services Team is responsible for the developer platform, and the impressive Amazon AWS estate Vortexa uses to achieve its purpose. Th...