Data engineering operates production pipelines that ingest, transform, and serve data across every product in our ecosystem. Event streaming architecture, structured data warehousing, and real-time analytics views give every team access to the intelligence they need to make fast, informed decisions.

AI and ML systems are deployed and serving users today. The Aspect generates personalized daily content using large language models orchestrated through custom prompt engineering pipelines with astronomical ephemeris data as input. Live broadcast systems run real-time audience sentiment analysis and engagement prediction models that inform production decisions mid-show.

We work with specialized data domains that require both engineering depth and subject-matter expertise: astronomical ephemeris calculations with sub-arcminute precision, real-time audience behavior modeling across concurrent streaming sessions, content performance prediction, and multi-channel revenue attribution. The data sources vary; the engineering rigor is consistent.

Privacy and data ethics are architectural constraints, not compliance checklists. Our data systems are designed with user consent management, data minimization principles, GDPR and CCPA compliance patterns, and audit logging built into the infrastructure layer. Trust is a product feature that we engineer deliberately.