Graph Engineer​/Ontologist

Location: Glasgow, Scotland, United Kingdom

Work Arrangement: Hybrid — 3 days per week in the office

Company: Morgan Stanley (subject to authorisation to advertise on its behalf)

Employment Type: To be confirmed

Morgan Stanley is seeking a Graph Engineer / Ontologist to support the design, development, and implementation of enterprise knowledge graphs and semantic data solutions.

The successful candidate will translate complex business, operational, financial, and regulatory concepts into robust ontologies, graph data models, and reusable semantic data products. These solutions will improve data discovery, integration, governance, lineage, and analytics across the organisation.

You will collaborate with data engineers, software developers, architects, subject-matter experts, risk and compliance teams, and business stakeholders to deliver scalable graph-based solutions within a highly regulated financial-services environment.

• Design, develop, and maintain enterprise knowledge graphs, ontologies, taxonomies, and semantic information models.
• Translate business, operational, financial, and regulatory requirements into formal ontology and graph specifications.
• Define entities, relationships, attributes, constraints, classifications, and semantic rules.
• Develop graph data models using technologies and standards such as RDF, RDF-star, OWL, SKOS, SHACL, SPARQL, property graphs, and Cypher.
• Build data ingestion and mapping pipelines using relational databases, APIs, documents, and other enterprise data sources.
• Integrate graph solutions with data platforms, metadata catalogues, data-quality tools, and analytical applications.
• Establish ontology governance practices covering version control, change management, documentation, reuse, and lifecycle management.
• Collaborate with domain experts to develop consistent representations of financial, legal, organisational, risk, and regulatory concepts.
• Implement validation rules and quality controls to ensure data accuracy, completeness, consistency, and traceability.
• Write and optimise graph queries and data-transformation pipelines.
• Support graph-based search, entity resolution, data lineage, impact analysis, data discovery, and analytics.
• Contribute to technical design reviews, engineering standards, testing, deployment, and operational support.
• Produce technical documentation, modelling guidelines, and user documentation.
• Promote best practices in semantic modelling, metadata management, data governance, and responsible data use.
• Keep up to date with developments in knowledge graphs, semantic technologies, AI, data architecture, and financial-services regulation.

• Demonstrable experience in graph engineering, ontology development, semantic modelling, knowledge representation, or a related discipline.
• Strong understanding of data modelling principles and information architecture.
• Practical experience with one or more semantic technologies, including RDF, OWL, SKOS, SHACL, or SPARQL.
• Experience with graph databases or platforms such as Neo4j, Amazon Neptune, Stardog, GraphDB, Allegro Graph, or equivalent technologies.
• Familiarity with graph query languages such as SPARQL or Cypher.
• Experience in data integration, ETL/ELT pipelines, APIs, relational databases, and structured or semi-structured data.
• Proficiency in at least one programming language, such as Python, Java, or Scala.
• Ability to translate complex business requirements into clear, maintainable conceptual and logical data models.
• Understanding of ontology design principles, including reuse, modularity, alignment, extensibility, and governance.
• Experience collaborating with cross-functional stakeholders and communicating technical…