Data Architect

Location: Raritan, NJ – Onsite

Data Architect, Regulatory Strategy

 Partner with Regulatory subject matter experts, development partners, product technical owners and engineers,

Technology Services, Data Sciences and fellow Pharma architects to design scalable, extensible and supportable data

architectures that drive business value in support of Regulatory Strategy and Intelligence

 Develop data architecture artifacts in collaboration with key stakeholders using standard tooling: Data Flow

Diagrams, Entity Relationship Diagrams, Data Integration Artifacts, etc.

 Responsible for the architectural alignment of Regulatory data products with Regulatory, R&D, Innovative Medicine

and Enterprise data and data platform strategies, defining and leveraging proven patterns and standards.

 Regularly engage with key business leaders and technical teams to pilot and leverage standard platforms to drive

data quality, standardization and interoperability in support of Regulatory Strategy and cross-domain initiatives,

including product master data alignment and interoperability, ontology management, graph/RAG and cataloging

capabilities to form a semantic layer to drive contextualization and speed to value of Regulatory data assets.

 Develop and maintain conceptual, logical and physical data models associated with Regulatory Strategy solutions.

 Assist the Regulatory Data Office in the development of a data governance framework that includes policies for the

creation, maintenance and stewardship of master data, reference data and critical data elements.

 Collaborate with business stakeholders to gather and translate their data needs into functional and technical

architecture.

 Advocate for data-driven decision-making by providing insights and recommendations based on data analysis and

architecture principles.

 Address and resolve conflicts arising from diverse business unit requirements, ensuring smooth integration of

stakeholder needs

 Serve as a coach to the Regulatory Data Office, Data Sciences and Technology product team partners to shape

strategy through sharing expertise in data governance, data quality, and data integration practices.

 Proactively identify opportunities for leveraging Regulatory data and contents an asset to enhance business

capabilities and drive competitive advantage.

 2+ years developing content vectorization and graph/RAG strategies in support of generative AI initiatives

Education:

 BA/BS degree in a technical, engineering or scientific field

 AWS Data Engineer Certification (or Azure/GCP equivalent)

 Experience with Snowflake and Denodo preferred

 AWS Well-Architected Framework certification preferred

 AWS Certified Machine Learning Specialty certification preferred