Job Summary:
Client is seeking a Graph Engineer / Ontologist to support the design, development, and implementation of enterprise knowledge graphs and semantic data solutions. The role will involve translating complex business and regulatory concepts into robust ontologies, graph models, and reusable data products that improve data discovery, integration, governance, and analytics across the organization.
The successful candidate will work closely with data engineers, software developers, architects, subject-matter experts, risk and compliance teams, and business stakeholders to create scalable graph-based solutions in a highly regulated financial-services environment.
Key Responsibilities:
· Design and develop knowledge graphs, ontologies, taxonomies, and semantic information models.
· Translate business, operational, financial, and regulatory requirements into formal graph and ontology specifications.
· Define entities, relationships, attributes, constraints, classifications, and semantic rules.
· Develop graph data models using appropriate standards and technologies, such as:
RDF and RDF-star
OWL and SKOS
SHACL
SPARQL
Property-graph models and Cypher
· Build data-mapping and ingestion processes from relational databases, APIs, documents, and other enterprise data sources.
· Integrate graph solutions with data platforms, data catalogues, data-quality tools, and analytical applications.
· Establish ontology governance, including versioning, change management, documentation, reuse, and lifecycle management.
· Collaborate with domain experts to create consistent definitions of financial, legal, organizational, risk, and regulatory concepts.
· Develop validation rules and quality controls to ensure graph data is accurate, complete, consistent, and traceable.
· Write and optimize graph queries and data-transformation pipelines.
· Support graph-based search, lineage, impact analysis, entity resolution, data discovery, and analytics use cases.
· Contribute to technical design reviews, engineering standards, testing, deployment, and operational support.
· Produce clear technical documentation, modelling guidelines, and user documentation.
· Promote best practices in semantic modelling, metadata management, data governance, and responsible use of data.
· Stay informed about developments in knowledge graphs, semantic technologies, AI, data architecture, and financial-services regulation.
Required Skills and Experience:
· Experience in graph engineering, ontology development, semantic modelling, knowledge representation, or a closely related discipline.
· Strong understanding of data modelling principles and information architecture.
· Practical experience with one or more of:
RDF, OWL, SKOS, SHACL, SPARQL
Neo4j, Amazon Neptune, Stardog, GraphDB, AllegroGraph, or similar graph platforms
Cypher or other graph-query languages
· Experience with 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 analyze complex requirements and represent them in clear, maintainable conceptual and logical models.
· Understanding of ontology design principles, including reuse, modularity, alignment, extensibility, and governance.
· Experience working with cross-functional stakeholders and explaining technical concepts to non-technical audiences.
· Strong problem-solving, analytical, 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, LEI, or other recognized data standards.
Experience with data lineage, metadata management, master data management, data catalogues, or data governance.
Familiarity with cloud…