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Reference Data Specialist
Amgen
Hyderabad, IND
Full-time
Senior · 8+ years experience
Onsite
Discovered 3 weeks ago
RDFOWLSKOSSPARQLSHACLLinked Data
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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 on the cutting-edge of innovation, using technology and human genetic data to push beyond what’s known today.
Role Description
Amgen is seeking an experienced Reference Data specialist to support enterprise semantic data, ontology, taxonomy, and knowledge graph initiatives across business and scientific domains. The role will focus on designing, developing, governing, and optimizing enterprise reference data and semantic models supporting analytics, interoperability, and data governance initiatives.
As the Reference Data Product team member of the Data Foundations & Governance organization, you will be responsible for managing and promoting the use of reference data, partnering with business Subject Mater Experts on creation of vocabularies / taxonomies and ontologies, and developing analytic solutions using semantic technologies.
Roles & Responsibilities
- Design, build and maintain enterprise ontologies, taxonomies, and semantic reference data models
- Collaborate with business SMEs, data architects, and governance teams to define semantic standards
- Contribute towards defining Reference data management framework for Enterprise
- Develop and optimize RDF/OWL/SKOS-based semantic frameworks and SPARQL/SQL queries.
- Support semantic data integration, metadata harmonization, and semantic publishing workflows.
- Manage ontology lifecycle activities including modeling, validation, versioning, and publishing.
- Collaborate with multiple enterprise & functional teams to elicit, structure and formalize knowledge from domain experts and diverse sources to build CVs, taxonomies, and ontologies.
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