Data & Information Architect

Career Category Information Systems Job Description ABOUT AMGEN Amgen harnesses the best of biology and technology to fight the world’s toughest diseases, and make people’s lives easier, fuller, and longer.

We discover, develop, manufacture, and deliver innovative medicines to help millions of patients.

Amgen helped establish the biotechnology industry more than 40 years ago and remains at the cutting edge of innovation, using technology and human genetic data to push beyond what is known today.

ABOUT THE ROLE You will play a critical role in advancing Amgen’s Operations Transformation and Digital Strategy by designing and delivering next-generation digital solutions that modernize how data, knowledge, and content are created, connected, governed, and consumed across the enterprise, in collaboration with the Operations Data Strategy Team.

This role is focused on applying information modeling, knowledge graphs, and Generative AI to solve complex business problems in a highly regulated environment.

The Data & Information Architect will help shape and scale AI-enabled solutions that support enterprise transformation, with particular emphasis on regulatory, operational, and data-centric use cases.

This role will contribute to initiatives that combine modern AI capabilities with structured content, knowledge graphs, and interoperable data models to enable intelligent automation, improved decision-making, and new ways of working.

This is an individual contributor role for a technically strong and strategically minded Data practitioner who can move from concept to proof of value and from prototype to scalable implementation while maintaining a strong commitment to responsible AI, compliance, and continuous improvement.

Role Description The Data & Information Architect is responsible for designing, developing, and scaling connected data solutions that combine data, context, generative AI, and enterprise data platforms to create measurable business value.

This role requires deep technical expertise, strong business engagement, and the ability to translate ambiguous business opportunities into production-oriented AI products and capabilities.

With a focus on pharmaceutical and operational data domains, the role involves applying data science, ontology-based modeling, knowledge graph methods, and modern AI technologies to build intelligent systems that can reason over connected data, generate insights, and automate knowledge-intensive tasks.

The role will work across structured and unstructured data, leveraging AWS, Databricks, OpenAI APIs, and related platforms to deliver scalable and compliant AI solutions.

This role will also help establish best practices in Connected Data, support transformation initiatives through experimentation and applied innovation, and promote a culture of continuous improvement in Data product delivery and business adoption.

Roles & Responsibilities Design, develop, and deploy connected data solutions using Information Modeling, Knowledge Graphs, and Generative AI, to address high-value business and operational challenges.

Build intelligent solutions that combine structured and unstructured data , semantic data models, and knowledge graph capabilities to improve automation, search, insight generation, and decision support.

Develop and scale proof-of-concept solutions in SQL and SPARQL and transition them into robust, enterprise-ready Data products for broader organizational use.

Apply SQL , R2RML , and other data transformation techniques to analyze, integrate, and prepare data from multiple enterprise sources.

Collaborate with business stakeholders, product teams, data engineers, architects, and domain experts to identify Data use cases and translate business requirements into scalable technical solutions.

Integrate FAIR data principles and data-centric design practices with AI to promote interoperability, discoverability, and governance of data assets.

Utilize Databricks and associated data/AI workflows to support experimentation, and model verification with real world data Ensure alignment with Responsible AI , security, privacy, and compliance expectations, including familiarity with emerging AI regulatory frameworks such as the EU AI Act .

Facilitate working sessions with stakeholders to clarify concepts, define success criteria, and align on transformation opportunities enabled by Data.

Contribute to the development of standards, reusable data products, and best practices for Model-driven design, semantic modeling, and product scaling.

Promote a culture of continuous improvement , innovation, and transformation by identifying opportunities to improve current processes, technologies, and ways of working.

Stay current with advancements in Knowledge Graphs , context engineering, agentic architectures, and regulatory expectations, and apply those insights pragmatically within the organization.

Basic Qualifications and Experience Master’s degree OR Bachelor’s degree with 4 to 7 years of experience in Data Science, Artificial Intelligence, Computer Science, Information Science, or related Functional Skills Must-Have Skills Strong hands-on experience in Information Modeling, Knowledge Graph development, and Generative AI, concepts and applications.

Proficiency in knowledge elicitation, data modeling for rapid prototyping, solution development, and scaling AI-driven capabilities.

Strong working knowledge of SQL for data analysis, transformation, and integration across enterprise systems.

Hands-on experience with Databricks or comparable data and AI platforms.

Strong understanding of integrated data, enterprise data ecosystems, and data-centric solution design.

Experience with knowledge graph and graph-based data platforms such as Stardog, GraphDB , or similar technologies.

Strong understanding of FAIR data principles and their application in enterprise and pharmaceutical data environments.

Ability to translate business concepts and requirements into models, semantic concep