Integrating API Data for Model Preparation

Imagine you are a machine learning engineer at a major financial institution, collaborating with a team responsible for generating input data for various downstream models. These models might include regulatory risk assessments, credit decision frameworks, internal risk evaluations, marketing strategies, audits, and any other ML-driven applications. You have access to the following APIs: - Reddit API for accessing posts and comments on finance and news-focused subreddits - Bloomberg API for obtaining daily stock market data, including opening and closing prices How would you architect an ML system to extract, transform, and store data from these APIs in a manner that is usable by downstream modeling teams?