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Amgen

Makes biotech medicines for serious illnesses

Data & Information Architect

Data ManagementConfirmed live in the last 24 hours
Full-timeHyderabad, Telangana, IndiaNo salary listedIn-person

About the Job

Requirements

  • A doctorate degree, or a master's or bachelor's degree with 5 to 8 years of experience in Data Science, Artificial Intelligence, Computer Science, Information Science, or a related field.
  • Strong hands-on experience in Information Modeling, Knowledge Graph development, and Generative AI concepts and applications.
  • Proficiency in knowledge elicitation and 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.
  • 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.

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 and 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 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.

Desired Qualifications

  • 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.

About the Company

Amgen

Makes biotech medicines for serious illnesses

Amgen develops and makes biologic medicines, which are drugs built from proteins and antibodies grown in living cells, for serious conditions such as heart disease, cancer, and bone loss. Its anemia drug Epogen, approved in 1989, became one of the biotechnology industry's first blockbuster medicines. Amgen grows these drugs in large tanks called bioreactors, and its products include the cholesterol drug Repatha, the bone-building drug Evenity, and the severe asthma drug Tezspire. It earns money by selling these medicines, mostly through large drug wholesalers that supply hospitals and pharmacies. Amgen was founded in 1980 and is based in Thousand Oaks, California.

Company size
10,001+
Company stage
IPO
Headquarters
Thousand Oaks, CA
Founded
1980

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