{"id":41350,"url":"https://alion.io/job/amgen-reference-data-specialist","title":"Reference Data Specialist","company":{"id":4775,"name":"Amgen","domain":"amgen.com","url":"https://alion.io/company/amgen","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":79,"open_postings":436,"ghost_share":0.002,"stale_share":0.833,"repost_share":0.007,"time_to_fill_p50_days":27,"computed_at":"2026-10-16T05:45:00Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Hyderabad, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":25000,"max_usd":52000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":59},"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"AWS","optional":false},{"name":"Databricks","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Git","optional":false},{"name":"GraphDB","optional":false},{"name":"Knowledge Graph","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"Rest API","optional":false},{"name":"SQL","optional":false},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-08-05T00:00:00Z","employer_posted_date":"2026-08-05","last_verified_at":"2026-10-16T19:08:41Z","board_verified":true,"closed_at":null,"days_open":72,"trust":{"level":"ok","repost_count":1,"flags":[],"days_open":72},"description":"Career Category\nInformation SystemsJob Description\nABOUT AMGEN\nAmgen 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.\nABOUT THE ROLE\nRole Description:\nAmgen 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.\nAs 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.\nRoles & Responsibilities:\nDesign, build and maintain enterprise ontologies, taxonomies, and semantic reference data models\nCollaborate with business SMEs, data architects, and governance teams to define semantic standards\nContribute towards defining Reference data management framework for Enterprise\nDevelop and optimize RDF/OWL/SKOS-based semantic frameworks and SPARQL/SQL queries.\nSupport semantic data integration, metadata harmonization, and semantic publishing workflows.\nManage ontology lifecycle activities including modeling, validation, versioning, and publishing.\nCollaborate with multiple enterprise & functional teams to elicit, structure and formalize knowledge from domain experts and diverse sources to build CVs, taxonomies, and ontologies.\nTroubleshoot semantic data load and mapping issues across Semantic Layer, CDL, and graph platforms.\nDevelop and optimize automated data ingestion / pipelines through Python/PySpark when APIs are available\nSupport enterprise Data Foundations, Knowledge Graph and Metadata Management initiatives.\nMentor junior engineers and provide technical leadership on semantic technologies.\nIdentify and resolve complex data-related challenges \nParticipate in sprint planning meetings and provide estimations on technical implementation.\nBasic Qualifications and Experience:\nMaster’s degree with 7- 10 years of experience in Business, Engineering, IT or related field OR\nBachelor’s degree with 8 - 12 years of experience in Business, Engineering, IT or related field OR\nFunctional Skills:\nMust-Have Skills:\nMandatory: 8-12 years of experience in Reference Data Engineering, Semantic Technologies, or Knowledge Graph implementations.\nAdvanced 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.\nHands-on experience with GraphDBs, TopBraid EDG, CenTree, MarkLogic, Stardog, or similar semantic platforms.\nStrong 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.\nStrong understanding of metadata management, reference data governance, and semantic interoperability.\nHands-on experience with modern data platforms such as Databricks and cloud engineering platforms such as AWS.\nExperience with APIs, JSON-LD, XML, SQL, and semantic integration frameworks.\nStrong analytical, troubleshooting, and stakeholder management skills.\nFamiliarity with FAIR Data Principles, Semantic Layer, metadata repositories, data catalogs and semantic publishing pipelines.\nExposure to enterprise knowledge graph and AI/ML initiatives.\nExperience working in Agile delivery models and cloud-based ecosystems.\nTechnical Skills:\nSemantic Technologies: RDF, OWL, SKOS, SPARQL, SHACL, Linked Data, JSON-LD\nPlatforms & Tools: GraphDB, TopBraid, CenTree, MarkLogic, Protégé, Semaphore, Databricks\nData & Integration: SQL, PySpark, ETL, Git, REST APIs, XML, JSON, Metadata & Data Governance \nProfessional Certifications:\nDatabricks Certificate preferred \nSAFe® Practitioner Certificate preferred \nAny Data Analysis certification (SQL, Python)\nAny cloud certification (AWS or AZURE)\nSoft Skills:\nStrong analytical abilities to assess and improve master data processes and solutions.\nExcellent verbal and written communication skills, with the 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