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, andGenerative 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 concepts, and data solutions.
Good-to-Have Skills
Experience with regulatory data, regulatory submission processes, or compliance requirements in the pharmaceutical domain.
Familiarity with the pharmaceutical lifecycle of data, including development, manufacturing, regulatory, and operational domains.
Knowledge of data modeling and knowledge graph concepts.
Experience integrating data from sources such as clinical, laboratory, manufacturing, quality, or regulatory systems.
Familiarity with healthcare and life sciences standards such as FHIR, IDMP, or related interoperability frameworks.
Familiarity with product-oriented delivery and scaling data proofs of concept into operationalized enterprise capabilities.
Soft Skills
Exceptional interpersonal, communication, facilitation, and business analysis skills.
Strong analytical thinking and structured problem-solving skills, especially in complex and regulated environments.
Ability to manage ambiguity, think strategically, and convert emerging opportunities into practical solutions.
Strong ability to prioritize and manage multiple initiatives in a dynamic setting.
Demonstrated customer- and user-centric product design mindset.
Strong collaboration skills with cross-functional, global, and multidisciplinary teams.
Ability to influence without authority and build alignment across technical and business stakeholders.
Passion for continuous improvement, innovation, and transformation.
Strong ownership mindset with the ability to independently drive high-impact work from concept through implementation.
EQUAL OPPORTUNITY STATEMENT
Amgen is an Equal Opportunity employer and will consider you without regard to your race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or disability status.
We will ensure that individuals with disabilities are provided with reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request an accommodation.
