Задачи
•Lead workshops and discovery sessions with business and technical stakeholders to elicit, define, and document business entities, relationships, attributes, hierarchies, and competency questions
•Develop and maintain enterprise ontologies, taxonomies, controlled vocabularies, and semantic models
•Map source systems and business concepts into canonical semantic representations
•Design, develop, and maintain scalable ELT/ETL frameworks, graph-loading processes, and semantic transformations supporting structured, semi-structured, and unstructured data
•Implement and optimize graph databases, semantic layers, and metadata repositories to support RAG, Knowledge Graph, and Agentic AI solutions
•Establish ontology governance frameworks and manage the business glossary and semantic versioning
•Automate data quality validation, monitoring, lineage, and observability processes
•Partner with Data Architects, Solution Architects, Data Stewards, and AI Engineers to ensure semantic consistency, discoverability, and high data quality across enterprise data products
Требования
•Bachelor's or Master's degree in Computer Science, Information Systems, Data Science, Engineering, or a related field
•5+ Years of combined professional experience in Data Engineering, Data Architecture, Knowledge Engineering, or Semantic Technologies
•Expertise in semantic web technologies (RDF, OWL, SPARQL), SKOS, SHACL, ontology development, taxonomy creation, and knowledge graph architecture
•Proficiency in building enterprise-scale ELT/ETL pipelines and data integration frameworks
•Familiarity with cloud data platforms such as Databricks, Snowflake, Azure, or AWS
•Advanced coding skills in Python and SQL, alongside graph querying and reasoning capabilities
•Understanding of modern AI patterns, including RAG architectures, vector databases, LLM integrations, and agentic AI systems
•Knowledge of metadata management, data quality, lineage, governance principles, and semantic versioning
•Exceptional verbal and written communication skills, with the ability to articulate complex semantic and data concepts clearly to diverse technical and non-technical stakeholders
•English proficiency at an Upper-Intermediate level (B2) or higher
Nice to have: background in semantic tech (RDF, OWL, SPARQL), SKOS, SHACL, and Knowledge Graphs; familiarity with AWS, Neo4j, and Amazon Neptune; skills in vector databases, semantic layer platforms, and RAG integrations
Условия
No conditions specified
