With data teams' growing ambition to build business automation, AI systems, or customer-facing products, we must shift our mindset about data quality. Mechanically applied testing will not be enough; we need a more robust strategy similar to software engineering. In this talk, I outline a new approach to data testing and observability anchored in the ‘Data Products’ concept and walk through the practical implementation of a production-grade analytics system with dbt as the backbone. The learnings will apply to data practitioners using dbt whether they're just getting started or working in a large enterprise.