How Moderna uses dbt Mesh to foster collaboration and streamline data engineering

Delivering life-saving medicines worldwide requires more than scientific precision—it demands sophisticated data infrastructure. For Moderna, this meant finding new ways to connect data across multiple platforms and teams. Their implementation of dbt Cloud with dbt Mesh enabled faster data velocity without data quality compromises.

Managing data across a global pharmaceutical supply chain

From pandemic response to data complexity

When Moderna became a household name during the pandemic, their data needs exploded. With over 5,000 employees across 17 countries and millions of mRNA vaccine doses being manufactured and distributed globally, they faced unprecedented scaling challenges.

The stakes were uniquely high. Vaccines require precise temperature control and timing, with costly consequences for any miscalculation. A single delayed shipment or temperature deviation could impact thousands of doses—and the patients waiting for them.

Three barriers to efficient data flow

Moderna’s data team identified three challenges affecting its data operations:

Data accessibility and availability

Moderna needed to break down data silos and enable teams across manufacturing, supply chain, and distribution to self-serve on accurate, real-time data to make decisions.

Data governance and compliance

As a licensed pharmaceutical company, Moderna needed to ensure that every data point was traceable, secure, and compliant with regulations across multiple jurisdictions. Data transparency, cleansing, and standardization were also essential to produce data everyone could trust.

Scalable infrastructure

Beyond immediate needs, Moderna needed a future-proof data platform that could scale to support increasingly sophisticated analytics, data science initiatives, and emerging AI applications while still managing costs.

Tackling data challenges with five data mesh principles

Moderna embraced data mesh principles to solve these challenges and implemented them with the help of dbt Cloud.

Data domain ownership

Moving away from a centralized data team, Moderna organized its data teams around business domains. Each domain had their own dbt project, giving them autonomy to support their use cases.

Data as a product

Moderna used dbt Mesh to join data from disparate data warehouses and create purpose-built data sets. dbt Cloud features like data lineage and out-of-box documentation created a common foundation among teams.

Self-service data platform

With accurate and readily available data, domain experts could leverage their own tools to deliver valuable insights autonomously, enabling faster development cycles.

Federated data governance

While teams gained autonomy, automated checks and guardrails were set in dbt Cloud—such as enforced metadata standards—to ensure consistent data quality.

Data and platform discoverability

The Mesh architecture made it easy for teams to discover and use data across platforms: from data lakes to Redshift.

Validating the new data infrastructure in a supply chain project

Preventing vaccine shortages and waste

A critical project put this new architecture to the test. The data team was tasked with building a visibility dashboard for the supply chain team. Success meant ensuring optimal vaccine delivery to pharmacies—preventing both costly overshipping and dangerous shortages.

Connecting three types of domain data across two different platforms

The solution required integrating data from three disparate business domains:

1. Supply chain operations managing inventory and distribution
2. Shipping logistics tracking delivery status and routes
3. Manufacturing data monitoring production schedules and output

This data was scattered across their Athena and Redshift environments.

Streamlined data engineering workstream

Without dbt Mesh, Moderna would’ve had to duplicate the data across the two environments. This would have led to redundancy, increased costs, more pipelines, and a loss of data lineage.

Instead, Moderna could combine ‌data from different domains and environments into a single dbt project. This streamlined software engineering, maintained the data lineage, and ensured the project’s timely delivery.

Three data learnings from Moderna

To those in similar data journeys, Sri Kamireddy, Principal Cloud Architect, Data and Analytics at Moderna, shares three key principles:

1. A data platform is the foundation of any organization. Without it, there’s no data success
2. Strong data governance and security are necessary to foster efficient collaboration
3. A scalable infrastructure helps keep costs under control

Transforming pharmaceutical DataOps

Moderna's adoption of dbt Mesh enabled it to unite critical data across platforms and decrease data silos while maintaining pharmaceutical-grade governance. The result was faster development cycles, improved data quality, and reliable vaccine delivery to patients worldwide.

Find out how dbt Cloud can accelerate your digital transformation and streamline data operations—contact us for a demo today.

Watch Moderna's session at AWS re:Invent to learn more about how they optimized vaccine delivery with dbt Mesh.