Graph Engineer / Ontologist

Financial Services Company; Glasgow; On-site; GBP 90,000 - 120,000; Full time

Job summary

Morgan Stanley in Glasgow is seeking a Graph Engineer / Ontologist to design, develop, and implement enterprise knowledge graphs and semantic data solutions. You will translate complex business, regulatory, and financial concepts into robust ontologies and graph models for improved data discovery, governance, and analytics.

You will collaborate with data engineers, architects, risk and compliance teams, and business stakeholders to deliver scalable graph-based solutions in a regulated

Qualifications

• Experience in graph engineering and ontology development.
• Strong data modelling and information architecture understanding.
• Practical experience with semantic technologies (RDF/OWL/SKOS/SHACL/SPARQL).
• Experience integrating graph solutions with data platforms and governance.

Responsibilities

• Design, develop, and maintain enterprise knowledge graphs and ontologies.
• Translate business requirements into formal ontology and graph specifications.
• Define entities, relationships, attributes, and semantic rules.
• Develop graph data models using RDF, OWL, SKOS, SHACL, SPARQL, and property graphs.
• Build data ingestion and mapping pipelines from various enterprise data sources.
• Ensure governance, version control, documentation, and lifecycle management.
• Collaborate with domain experts to model financial, regulatory concepts.
• Write and optimize graph queries and data-transformation pipelines.
• Support graph-based search, data lineage, and analytics.

Skills

Graph engineering

Ontology development

Semantic modelling

Knowledge representation

Data modelling

Python/Java/Scala

SPARQL/Cypher

Communication to non-technical

Security and governance

Education

Bachelor’s degree in CS/IS/Data Science

Tools

Neo4j

Amazon Neptune

Stardog

GraphDB

AllegroGraph

Job description

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

Job Summary

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.

Key Responsibilities

• 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.

Required Skills and Experience

• 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, AllegroGraph, 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 concepts to non-technical audiences.
• Strong analytical, problem-solving, communication, and documentation skills.
• A disciplined approach to security, data quality, controls, and operational risk.

Desirable Skills

• Experience in banking, capital markets, financial services, risk, compliance, or regulatory data.
• Knowledge of financial-industry standards and reference models, such as FIBO, ISO 20022, and Legal Entity Identifiers (LEIs).
• Experience with data lineage, metadata management, master data management, data catalogues, or data governance.
• Familiarity with cloud platforms, containerisation, CI/CD, and infrastructure as code.
• Experience with entity resolution, natural-language processing, machine learning, or graph-based AI applications.
• Knowledge of software engineering best practices, automated testing, code reviews, and agile delivery.
• Experience supporting enterprise-scale platforms with high availability, security, and performance requirements.
• A relevant degree or equivalent professional experience in computer science, information systems, data science, mathematics, engineering, or a related field.

Work Arrangement

This role is based in Glasgow and requires working from the office three days per week. Candidates should be able to meet this on-site requirement.