SiriusXM, the leading audio entertainment company in North America, recently rebuilt its streaming app on an event-driven architecture powered by Databricks. In this fireside chat, Armen Zaybekian, VP of Data Quality and Data Standards at SiriusXM, shares how SiriusXM embedded data observability to ensure quality at scale from day one. This includes automatically discovering new tables, applying freshness and volume checks, building metrics checks, and validating critical migrations with comparison monitors. Armen highlights how data observability safeguards trust for 500+ data users across Finance, Marketing, Analytics, Customer Care, and Data Science. By rapidly detecting and communicating issues, SiriusXM minimizes impacts to marketing campaigns, financial reporting, and royalties. Armen will also explore how ML-driven adaptive thresholds, flexible data source coverage, and deep integrations reduce upkeep and minimize alert fatigue across both new and legacy data pipelines.