Overview

This role focuses on defining the target architecture for clinical and real world data and guiding the clinical data platform strategy. You will own the canonical and clinical data models, build the semantic layer, and shape the data quality framework across the platform. You will work closely with stakeholders and lead PoC initiatives to validate ideas before full scale implementation. Project Overview: You will work on a modern clinical and real world data platform designed to integrate EHR, EDC, lab data, and registries into a shared clinical model. The goal of the project is to build a scalable architecture with a strong focus on data models, ontology, semantic layers, and platform wide data quality.

Responsibilities:
  • Design and evolve enterprise level clinical and canonical data models for key domains
  • Define and maintain the ontology and semantic layer including concepts, relationships, and metrics
  • Architect a data quality framework with rules, checks, and monitoring embedded into pipelines
  • Lead architecture driven PoCs on Databricks to validate new models, ontologies, and data quality patterns using real data
  • Communicate architecture options, trade offs, and decisions to business, clinical, and technical stakeholders
  • Provide guidance to data engineers and analysts on implementing the target architecture and standards
Required Qualifications:
  • Seven years of experience in data architecture or data engineering with strong focus on modeling and platform design
  • Experience designing canonical and domain models ideally for clinical research, healthcare, or pharma
  • Experience with ontology and semantic layer design for analytics and data products
  • Experience defining or implementing a data quality framework including rules and monitoring
  • Hands on experience delivering PoCs end to end and transforming them into architectural standards
  • Strong communication skills including workshops, requirements clarification, and architecture presentations
Nice To Have:
  • Background in clinical research or pharma tech including familiarity with clinical data standards and terminologies
  • Experience leading or mentoring other architects or senior data engineers
Note:

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