How a healthcare startup migrated from Azure to GCP and kept production running

Jo Hjersman has spent over five years at a healthcare XR startup wearing every hat on the data stack, from research data scientist to Head of Data. In this episode, he walks Saket through how he built and scaled a behavioral analytics platform for mental health care, navigated a full cloud migration from Azure to GCP with critical systems kept online throughout, and keeps the whole system running efficiently on a startup budget.The conversation gets into the real mechanics: how intent-driven data design changes what you can extract from immersive environments, how to handle schema evolution without breaking downstream consumers, and why the data scientist and ML engineer roles are converging toward an ownership model rather than a specialization model.Topics discussed:Designing intent-driven data capture in immersive healthcare environmentsBuilding a bronze/silver/gold architecture from scratch at a startupManaging schema evolution across multi-device data sourcesPlanning and executing a full Azure-to-GCP cloud migration with minimal downtimeHandling HIPAA-adjacent compliance through UUID abstraction at the schema levelWhy data scientists and ML engineers are converging toward a full-stack ownership modelWhat bootcamps miss about real-world data engineering at scaleEvaluating infrastructure trade-offs from both a technical and business cost perspective