Enterprise Data Architect - AI-Ready & Real-Time OT/IT

BioSpace; Norwood (MA); On-site; USD 146,000 - 234,000; Full time

Benefits offered by this job

Competitive healthcare

Well-being resources

Family planning benefits

Generous PTO

Job summary

Moderna is seeking a Principal Data Architect to design and steward the enterprise data architecture, enabling AI-ready, governable data at scale across Manufacturing, Quality, and Supply Chain. You will define patterns, data models, metadata standards, and reusable artifacts, integrate real-time OT data with IT platforms, and set templates for teams to build trusted data products.

As a senior contributor, you’ll influence technical direction, mentor engineers, and drive consistency across the

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field.
• 7+ years of experience in data architecture, data engineering, or enterprise architecture.
• 4+ years of experience supporting pharmaceutical, biotech, manufacturing, or other regulated environments.
• Experience integrating data from control systems, automation environments, or real-time operational data sources.
• Experience designing data architectures that span operational systems and analytical platforms, connecting source systems to governed, reusable data products.
• Integration architecture experience across enterprise systems, including ERP, QMS, MES, LIMS, or equivalent.
• Strong understanding of data modeling, both dimensional and entity-relationship approaches, applied to operational and analytical use cases.
• Proven ability to produce architecture specifications that engineering teams can implement directly.
• Strong understanding of data governance mechanics, including lineage, access control, data classification, and retention.
• Understanding of GxP, data integrity, and compliance considerations and how they shape architectural decisions.

Responsibilities

• Define and maintain the target-state data architecture across CMC domains, designing for composability with shared entities modeled once and domain-specific extensions layered on top
• Define and implement integration patterns that connect control systems and automation environments with enterprise data platforms, enabling real-time, event-driven data flows across OT and IT layers
• Establish repeatable patterns for ingesting, transforming, and serving data from heterogeneous CMC systems
• Define and enforce data standards, including naming conventions, classification, lineage, and metadata, treating metadata as a first-class architectural concern
• Design data models and semantic structures that support both analytics and AI use cases across CMC domains
• Codify architecture patterns as templates, reference implementations, and decision records, enabling teams to build from proven designs rather than starting from scratch
• Develop strategies for controlled vocabularies, business glossaries, and semantic models that make CMC data consistent and navigable across domains
• Inform cloud data platform decisions across warehousing, transformation, orchestration, and catalog tooling to ensure alignment with architectural standards
• Mentor engineers and data product owners, raising architectural fluency and design consistency across the CMC Digital organization

Skills

Data architecture

OT/IT integration

Data governance

Data modeling

Architecture docs

Education

Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field

Tools

dbt

Redshift

Snowflake

GitHub workflows

Job description

Moderna is seeking a Principal Data Architect to design and steward the enterprise data architecture, enabling AI-ready, governable data at scale across Manufacturing, Quality, and Supply Chain. You will define patterns, data models, metadata standards, and reusable artifacts, integrate real-time OT data with IT platforms, and set templates for teams to build trusted data products.

As a senior contributor, you’ll influence technical direction, mentor engineers, and drive consistency across the