How Verily Health monitors wastewater for 30-plus pathogens with a 5-person team and 1 dbt package

Verily Health uses a five-person data team and a shared dbt package to support near real-time wastewater surveillance for more than 30 pathogens, supplying its public Sightline dashboard as well as researchers, government agencies, and the CDC with data typically delayed by only one or two days. Built on the FHIR healthcare interoperability standard, the team manages deeply nested clinical and laboratory data by using parameterized dbt macros that can model resources such as observations across wastewater monitoring, diabetes care, weight-loss programs, and clinical trials without duplicating code. To keep models practical, the team generally limits composite keys to about three columns and tables to around 30 columns, accepting less granular data models when needed. Its medallion-style pipeline moves from restricted bronze data through FHIR-aligned staging and optional intermediate testing layers to domain-focused marts designed for scientists and researchers, while dbt freshness tests monitor diverse partner data formats. Documentation and dbt’s semantic layer enable self-service access for a broad stakeholder base, and the system was used to expand surveillance to World Cup host cities, where no major outbreaks were reported during the tournament.

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