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Senior Knowledge Graph Engineer

🕒 Outubro 19

🇺🇸 Estados Unidos – Remoto (EUA)

⏰ Tempo Integral

🟠 Sênior

👷🏻‍♀️ Engenheiro

🗣️🇺🇸🇬🇧 Inglês obrigatório

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Publicada na página de carreiras da Quantiphi, não em um site de vagas

Vista pela primeira vez pelo Remote Rocketship Outubro 19

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Quantiphi

1001 - 5000 funcionários

Fundada em 2013

💼 Consultoria

🏥 Saúde

📦 Logística

💰 Series A em 2019-12

Consulting • Healthcare • Logistics

A Quantiphi é uma empresa líder em engenharia digital orientada por IA que utiliza uma década de experiência no setor para capacitar negócios por meio de soluções de IA escaláveis, seguras e adaptáveis. Ao integrar tecnologia de ponta com aplicações do mundo real, a Quantiphi transforma organizações em vários setores, incluindo saúde, finanças, educação e varejo. Seus serviços abrangem aplicações de IA, análises de dados, modernização de infraestrutura em nuvem e implementações personalizadas de IA. A Quantiphi faz parcerias com gigantes da tecnologia como AWS, Google Cloud, NVIDIA e outros para impulsionar a adoção de IA e oferecer oportunidades transformacionais para empresas.

Descrição

• Develop, implement, build, and maintain production knowledge graph solutions across LPG and RDF graph technologies • Build scalable pipelines to transform healthcare/FHIR data into appropriate graph representations • Implement mappings between patient/clinical data and concepts represented in the clinical ontology • Develop reusable mapping and transformation patterns rather than one-off implementations • Implement consistent approaches for entity identity, canonical identifiers/URI/IRI, relationships, and concept linking • Maintain provenance and traceability between source data, mapping rules, and resulting graph entities and relationships • Develop and optimize graph queries using Cypher and/or SPARQL • Implement automated validation and testing to identify unresolved mappings, inconsistent relationships, and other graph-quality issues • Work with ontology, FHIR, terminology, and clinical SMEs to clarify ambiguous or missing mapping requirements • Participate in technical design, architecture reviews, code reviews, and engineering best practices

🎯 Requisitos

• 5+ years of software/data engineering experience, including hands-on experience with knowledge graphs or graph technologies • Strong understanding of knowledge graph and graph data modeling concepts • Hands-on experience with Labeled Property Graphs, such as Neo4j/Cypher or equivalent, or RDF/semantic technologies, such as RDF/RDFS, OWL, and SPARQL • Working knowledge of, or ability to work across, both LPG and RDF graph models • Strong programming skills in Python, Java, or similar languages • Experience building production data ingestion, transformation, or integration pipelines • Experience with graph databases and/or RDF triple stores • Understanding of entity identity, graph relationships, mappings, provenance, and data quality • Ability to translate conceptual models and mapping specifications into production implementations • Ability to work effectively with evolving requirements and cross-functional technical/domain teams • Hands-on experience with both LPG and RDF/semantic knowledge graphs • Healthcare or life sciences data experience • Familiarity with HL7 FHIR, including Coding, CodeableConcept, Reference, and Identifier • Experience with ontology-driven data integration or semantic mapping • Experience with SHACL or other graph/semantic validation approaches • Experience with terminology/concept normalization and canonical concept mapping • Familiarity with clinical terminologies such as SNOMED CT, LOINC, RxNorm, ICD, or UMLS • Cloud and CI/CD experience

🏖️ Benefícios

• Upskilling and professional development opportunities • Exposure to AI, ML, data, and cloud technologies • Opportunities to work with Fortune 1000 companies • Work in a research-focused organization with 60+ patents filed • Collaboration with talented colleagues • Remote work arrangement • Up to 25% travel to client sites across the US

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Desenvolvido por Lior Neu-ner. Adoraria receber seu feedback — entre em contato por DM ou pelo e-mail support@remoterocketship.com
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