Manager Data Architecture

Johnson & Johnson Innovative Medicine is recruiting for a Manager Data Architecture to lead the Data Catalog and Data Governance capabilities.

At Johnson & Johnson Innovative Medicine, what matters most is helping people live full and healthy lives. We focus on treating, curing, and preventing some of the most devastating and complex diseases of our time. And we pursue the most promising science, wherever it might be found.

The Data Catalog & Data Governance architect role is committed to make data accessible to all R&D associates, ensuring high-quality data, robust data pipelines, and streamlined data consumption. Specifically, we aim to:

• Collaborate with R&D business stakeholders and IT teams to understand cataloging objectives, challenges, and requirements.

• Develop Data governance, Data Catalog strategies and roadmaps in collaboration across various teams.

• Lead efforts in defining data management policies, standards, and best practices in collaboration across stake holders.

• Improve data findability and interoperability across domains.

• Enable domain experts and application owners to dynamically model, harmonize, and enrich relevant vocabularies and ontologies.

Key responsibilities:

In this position, you will be building partnerships within both business and IT. Your key areas of focus will be:

• Develop and recommend data architecture components in support of data catalogs, data governance, data pipelines and storage.

• Review of data models, data taxonomy and associated data domains, metadata, and business critical data to execute processes across the data control environment.

• Leverage data modeling techniques to design semantic and ontological models that enhance data understanding and alignment with business concepts.

• Create and maintain catalog content for all R&D data packages and data products.

• Shape and drive overall catalog and governance strategies.

• Together with business partners, model their space and integrate the model for annotating content with semantic entities, making them findable and interoperable.

• Build strategic capabilities to ensure internal consistency within the ontology modelling ecosystem and efficient extraction of semantic entities from content.

• Drive alignment to Enterprise and pharmaceutical R&D technology strategy, patterns, and standards.

• Define reference architecture, patterns and standard methodologies.

• Design, maintain and socialize solution architecture collaboration with Lead Engineers.

• Explore the benefits of combining large language models (LLMs) and generative AI with ontology modelling to improve semantic entity recognition and annotation.

• Define solution architects to identify and integrate suitable modular capabilities.