Data & Semantic Model Architect
TetraScience
Role Description
The Data & Semantic Model Architect will serve as the technical and strategic anchor for the "Semantic Layer" and the Common Data Model (CDM) of the Tetra Scientific Data and AI Cloud. You are the rare individual who can "do it all"—bridging deep technical semantics, system architecture, and business outcomes.
Crucially, you will be the owner of the Common Model & Exchange Layer of our platform: a set of unified, reusable common data models that allow data to flow seamlessly across different customer environments while driving towards true Ontology. You will define the data contracts and consistent definitions that empower our Forward Deployed Scientific Data Engineers & Architects (FDEs) to deliver rapid, reliable integrations without reinventing the wheel for every deployment. You will ensure our models are not just academically sound, but serve as the robust foundation for scalable data exchange and scientific insight.
What You Will Do
- Common Data Model & Exchange Strategy
- Architect the Exchange Layer: Design and own the Common Data Models (CDMs) that serve as the universal language for scientific data across our customer base.
- Empower Forward Deployed Engineering: Create the data contracts and standardized definitions that FDEs rely on.
- Standardization vs. Flexibility: Strike the strategic balance between rigid global standards and local flexibility.
- Semantic Architecture & Implementation
- The "Forest" – Business Alignment: Translate high-level business goals into concrete data modeling strategies.
- The "Trees" – Hands-on Modeling: Roll up your sleeves to design and implement complex ontologies and taxonomies.
- Software & Data Engineering Integration: Work directly with Engineering to architect the software systems that consume these models.
- Cross-Functional Leadership & Governance
- Data Contracts & Governance: Establish the "rules of the road" for data quality and consistency.
- Scientific Translation: Partner with Scientific Business Analysts to decode the complexity of biopharma R&D.
- Interoperability: Architect models that ensure our data is FAIR (Findable, Accessible, Interoperable, Reusable).
Qualifications
- Common Data Model Expertise: Proven ability to design shared data models that serve as an exchange format between different systems or organizations.
- Data Contract Design: Experience defining and enforcing data contracts in a microservices or platform environment.
- Architectural Versatility: The ability to switch context effortlessly between high-level system design and low-level entity relationship modeling.
- Semantic Fluency: Deep, hands-on expertise with semantic web standards (RDF, OWL, SHACL, SPARQL) and property graph concepts (LPG).
- 7+ years of experience in data architecture, informatics, or technical product leadership, specifically within life sciences, healthcare, manufacturing technology.
- CDM Framework Expertise: Direct, hands-on experience implementing and extending Common Data Model frameworks such as HL7 FHIR, OMOP (OHDSI), Allotrope, or CDISC.
- Terminology & Standardization: Proven mastery in standardizing messy, heterogeneous data using both standard vocabularies and proprietary or custom vocabularies.
- Platform & Exchange Experience: Experience building data platforms where standardization and reusability were key value drivers.
- Technical Background: Strong proficiency in software development concepts; comfortable reading code, understanding API contracts, and discussing database internals.
- Education: Bachelor's or Master’s in a relevant field (e.g., Medical Informatics, Computer Science, Bioinformatics, Physics).
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