pythonetlknowledge graphsrdfsparqlowlsemantic webontology engineeringlinked data
Вакансия из Hirify Global, списка международных tech-компаний Для мэтча и отклика нужен Plus
Пожаловаться
Зарплата и рынок
ЗП не указанаразвернуть
На похожих ролях по рынку
$69к$75кмедиана$79к
9 в выборке
На СНГ рынке: $3.7к/мес ($3.1к - $4.3к)
84
Хорошая вакансия
развернуть
У роли четкий фокус на семантических данных и подробно описан стек, но работа в сервисной компании может зависеть от проекта.
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Подключить Plus
Описание вакансии
Текст:
Hirify AI/Оригинал
TL;DR
Data Scientist - European Agency (Semantic Data): Designing and implementing semantic data, Linked Data, ontology, and knowledge graph solutions for heterogeneous information sources with an accent on interoperability, RDF-based transformations, and semantic validation. Focus on modelling ontologies, optimising SPARQL queries, building ETL/ELT pipelines, and validating data with SHACL.
Location: Remote; I. Kerület, Budapest, Hungary
Company
hirify.global is a digital transformation services company delivering international projects for clients across multiple sectors.
What you will do
Design and align semantic data models and ontologies, develop controlled vocabularies, and manage ontology lifecycles.
Design, maintain, and optimise knowledge graphs and SPARQL queries.
Develop ETL/ELT pipelines to ingest, transform, and publish data from relational databases, XML, JSON, CSV, and APIs into RDF environments.
Implement Linked Data solutions and semantic transformations using RDF standards and mapping technologies.
Translate business requirements into technical specifications and explain semantic data concepts to technical and non-technical stakeholders.
Requirements
Senior-level experience in data science, semantic data engineering, or a related field.
Expertise in semantic data, Linked Data, ontology engineering, and knowledge graphs.
Experience with RDF, RDFS, OWL, SKOS, SHACL, JSON-LD, Turtle, and RDF/XML.
Experience with SPARQL, knowledge graph modelling and optimisation, and platforms such as QLever, Virtuoso, or GraphDB.
Experience with ontology alignment, vocabulary design, ontology lifecycle management, and semantic modelling.
Python and ETL/ELT experience, including data ingestion and transformation from relational, XML, JSON, CSV, and API sources.
Knowledge of RML, semantic data validation, RDF mappings, and Linked Data interoperability.
Culture & Benefits
Remote work and a collaborative work environment.
High-impact international project supporting European institutions and agencies.
Career plan and training plan.
Flexible remuneration.
Будьте осторожны
Если работодатель просит войти в их систему, используя iCloud/Google, прислать код/пароль, запустить код/ПО, не делайте этого. Это мошенники. Обязательно жмите «Пожаловаться» или пишите в поддержку. Подробнее в гайде →