Data & Semantic Model Architect

Responsibilities

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. Move the platform from bespoke, one-off mappings to a standardized "exchange layer" that ensures interoperability.
• Empower Forward Deployed Engineering: Create the data contracts and standardized definitions that FDEs rely on. Your models will be the toolkit that allows them to deploy faster and with higher confidence.
• Standardization vs. Flexibility: Strike the strategic balance between rigid global standards (for cross-customer exchange) and local flexibility. Define the core "immutable" aspects of the model versus where extension is permitted.

Semantic Architecture & Implementation

• The "Forest" – Business Alignment: Translate high-level business goals into concrete data modeling strategies. Ensure our semantic roadmap directly supports the scientific questions our customers need to answer.
• The "Trees" – Hands-on Modeling: Design and implement complex ontologies and taxonomies. Model intricate scientific relationships with precision.
• Software & Data Engineering Integration: Work directly with Engineering to architect the software systems that consume these models. Ensure that the ontology does not break query performance or system scalability.

Cross-Functional Leadership & Governance

• Data Contracts & Governance: Establish the "rules of the road" for data quality and consistency. Define how data contracts are versioned, enforced, and evolved.
• Scientific Translation: Partner with Scientific Business Analysts to decode the complexity of biopharma R&D. Turn ambiguous scientific requirements into rigorous, machine-readable data structures.
• Interoperability: Architect models that ensure our data is FAIR (Findable, Accessible, Interoperable, Reusable) and ready for downstream AI/ML applications.

Skills & Competencies

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).

Requirements

• 7+ years of experience in data architecture, informatics, or technical product leadership, specifically within life sciences, healthcare, manufacturing technology or the ability to demonstrate complex, multidomain unification of data models & semantic layers.
• 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 (such as terminology standards & ontologies) as well as 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).">