Knowledge Graph Engineer - Investment Data Ontology

Summary
Contract role to design and deliver a proof-of-concept knowledge graph modeling investment fund data for one of the world's largest asset managers. You will encode business rules, regulatory constraints, and identifier relationships as machine-readable ontologies — directly eliminating manual fund data processes and enabling automated validation across thousands of funds in 6 global markets. Defined POC scope, executive sponsorship, and weekly technical guidance from two of the most recognized knowledge graph practitioners in financial services.
What You'll Deliver (POC Scope)
An investment fund ontology (OWL 2 / RDF / Linked Data) modeling the product hierarchy: Fund > ShareClass > Listing > Security, with 73+ identifier types (ISIN, SEDOL, CUSIP, LEI, Bloomberg, and more) governed across US, UK, Ireland, Australia, Canada, and Mexico
SHACL validation shapes encoding business rules as executable constraints — e.g., "A US-domiciled ETF listing must have a valid ISIN" — that flag violations at fund launch and throughout the fund lifecycle
SKOS concept schemes harmonizing vocabulary across 8+ internal systems, providing a semantic bridge between source-of-record platforms
Data integration pipelines mapping relational data into RDF triples (Turtle/N-Quads) using R2RML, rdflib, or equivalent mapping tooling
API layer enabling downstream applications to consume graph data programmatically
Automated governance reports surfacing data quality gaps, missing identifiers, and cross-system inconsistencies
Required Skills
5+ years hands-on experience building and deploying RDF/OWL ontologies in production (not solely academic — you have shipped something real)
SHACL for constraint validation, data quality enforcement, and shape-based governance
SPARQL 1.1 — fluent in complex queries, property paths, and federated queries
At least one enterprise triple store / graph platform: TopBraid, GraphDB (Ontotext), Stardog, RDFox, Amazon Neptune (RDF mode), or equivalent
Python or Java for data transformation, pipeline orchestration, and integration work
Familiarity with financial or securities identifiers (ISIN, SEDOL, CUSIP, LEI, or similar instrument identification schemes) — you don't need to be a fund accountant, but you need to understand what an identifier is and why it matters
Working knowledge of data governance — you understand why constraints exist, not just how to code them
Preferred Experience
Financial services domain: fund data, securities master, regulatory compliance (MiFID, UCITS, listing rules)
FIBO (Financial Industry Business Ontology) or similar financial ontologies
TopBraid EDG / GraphWise (our target platform — evaluation input from this hire is welcome)
SKOS for vocabulary management and cross-system term harmonization
R2RML / RML or equivalent relational-to-RDF mapping standards
Ontology design patterns, modular schema design, ontology versioning (Git-based workflows)
Enterprise-scale data modeling (thousands of entities, multi-market, multi-product-type)
Exposure to rules engines, inference, or deterministic AI (SHACL-based reasoning, business rules automation)
Agile delivery in a regulated environment

How We Work

Vanguard has implemented a hybrid working model for the majority of our crew members, designed to capture the benefits of enhanced flexibility while enabling in-person learning, collaboration, and connection. We believe our mission-driven and highly collaborative culture is a critical enabler to support long-term client outcomes and enrich the employee experience.