Reference Data Specialist

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.

Troubleshoot semantic data load and mapping issues across Semantic Layer, CDL, and graph platforms.

Develop and optimize automated data ingestion / pipelines through Python/PySpark when APIs are available

Support enterprise Data Foundations, Knowledge Graph and Metadata Management initiatives.

Mentor junior engineers and provide technical leadership on semantic technologies.

Identify and resolve complex data-related challenges

Participate in sprint planning meetings and provide estimations on technical implementation.

Basic Qualifications and Experience:

Master’s degree with 7- 10 years of experience in Business, Engineering, IT or related field OR

Bachelor’s degree with 8 - 12 years of experience in Business, Engineering, IT or related field OR

Functional Skills:

Must-Have Skills:

Mandatory: 8–12 years of experience in Reference Data Engineering, Semantic Technologies, or Knowledge Graph implementations.

Advanced knowledge of ontologies and taxonomies with proficiency in Semantic Web technologies, standards and tools such as RDF/s, OWL, SKOS, SPARQL, SHACL, and Linked Data standards.

Hands-on experience with GraphDBs, TopBraid EDG, CenTree, MarkLogic, Stardog, or similar semantic platforms.

Strong expertise in Pharma Domain CVs/Taxonomies/Ontologies such as CDISC, MedDRA, WHODrug, NCIT, IDMP SPOR, SNOMED CT, ICD 10/11 etc. and integrating them into enterprise-wide applications.

Strong understanding of metadata management, reference data governance, and semantic interoperability.

Hands-on experience with modern data platforms such as Databricks and cloud engineering platforms such as AWS.

Experience with APIs, JSON-LD, XML, SQL, and semantic integration frameworks.

Strong analytical, troubleshooting, and stakeholder management skills.

Familiarity with FAIR Data Principles, Semantic Layer, metadata repositories, data catalogs and semantic publishing pipelines.

Exposure to enterprise knowledge graph and AI/ML initiatives.

Experience working in Agile delivery models and cloud-based ecosystems.