Principal Data Architect, CMC Digital
$145.9k - $234.2kModerna
The Role The Principal Data Architect will design and steward the enterprise data architecture that makes CMC data usable, governable, and AI-ready at scale. This role defines integration patterns, data models, metadata standards, and reusable architecture artifacts that enable consistent, scalable delivery of data products across Manufacturing, Quality, and Supply Chain operations. A core focus is enabling the integration of real-time data from control systems and automation environments into a unified, event-driven architecture that bridges OT and IT data, requiring deep understanding of manufacturing and automation processes. CMC data spans systems with diverse structures, semantics, and quality characteristics. This role brings coherence to that complexity by designing patterns that normalize heterogeneous data into a platform where analysts, engineers, and AI systems can operate with confidence. As a principal-level contributor, this individual operates with significant autonomy, influences technical direction across CMC Digital, and builds the architectural foundations that enable consistent, reusable, and scalable data and AI capabilities across the enterprise. Here's What You'll Do
- 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
- 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
- Direct experience with Veeva Quality, LabVantage, Syncade, or similar MES and LIMS platforms and their data structures
- Experience with OT/IT integration architecture, including MES, DCS, SCADA, or historian systems in a regulated environment
- Familiarity with manufacturing data standards and how they inform enterprise data architecture decisions
- Experience with SAP data domains and integration patterns for manufacturing and supply chain data
- Hands-on experience with dbt, Redshift, Snowflake, or similar transformation and cloud data warehouse tooling
- Experience with metadata management, data catalog tooling, or business glossary programs at enterprise scale
- Experience designing multi-schema or multi-tenant architectures with fine-grained, policy-driven access control
- Exposure to knowledge graphs, ontologies, or semantic modeling applied to enterprise or scientific data
- Experience with GitHub-based workflows, architecture-as-code practices, or version-controlled specification and pattern management
- Experience with or strong interest in AI-ready data architecture, including how data models, semantic layers, and operational knowledge bases support agentic AI workflows
- Background in GxP validation readiness for data platforms and how architectural decisions affect future compliance posture
$168.5k - $206k
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