To support advanced analytics and machine learning use cases, we first needed to standardize and ingest highly variable, semi-structured Firebase and Apple Watch transaction data. The team prioritized building a scalable pipeline that could handle schema drift, support ML feature extraction, and deliver reliable datasets to data scientists. Our focus was on enabling real-time access, improving data quality, and ensuring that infrastructure remained flexible for evolving business needs.