Ontology Engineer

NWEA® is a division of HMH that supports students and educators through research, assessment solutions, policy and advocacy services, professional learning, and school improvement services that fight for equity, drive classroom impact, and push for systemic change in educational communities. For nearly 50 years, NWEA has developed innovative pre-K–12 assessments, including their flagship interim assessment, MAP® Growth™, and their reading fluency and comprehension assessment, MAP® Reading Fluency™.

About the role

The Ontology Engineer plays a pivotal role in shaping our organization's knowledge structure. They are responsible for developing and managing ontologies that underpin our information systems, facilitating better data organization and knowledge discovery.

Responsibilities

• Develops and maintains logical, semantically rich, and extensible ontologies that define and structure knowledge and underpin the K-12 education domain and HMH products.
• Supports integration between the ontology management system and source data management repositories, including triple store development and investigation by writing SPARQL queries against RDF, OWL or validating with SHACL.
• Ensures the accuracy and consistency of ontological structures by performing regular quality checks and updates as needed.
• Collaborates with cross-functional teams to understand their information needs and provide ontological solutions that support their objectives.
• Creates comprehensive documentation for ontologies and knowledge graphs, making them accessible to both technical and non-technical stakeholders.
• Coordinates with the Data engineering and operations, and content development teams to ensure the knowledge representation is aligned with enterprise data systems.

Requirements

• Advanced degree in philosophy, computer science, information science, or quantitative field, or equivalent experience.
• 2+ years of relevant work experience.
• Proficiency in ontology modeling languages such as RDF, OWL, or SHACL and vocabularies such as SKOS.
• Demonstrated advanced knowledge of ontology modeling languages such as RDF, OWL, or SHACL, and vocabularies like SKOS.
• Familiarity with query languages like SQL and SPARQL or other property graph query languages like Gremlin, openCypher.
• Experience with semantic data integration and using graph databases/triplestores, including modeling tradeoffs, query optimization, and operational considerations for production use.
• Experience with ontologies, knowledge graphs, and/or semantic technologies such as Stardog, Protégé, Semaphore, PoolParty, or related ontology management systems.
• Experience using foundational/top-level ontologies, especially Basic Formal Ontology (BFO), Descriptive Ontology for Linguistic and Cognitive Engineering (DOLCE), Common Core Ontologies, or OBO Foundry.
• Experience integrating multiple disparate data sets into a common vocabulary and writing effective queries for use in a production environment.
• Hands-on experience with high-level programming and scripting languages, such as Python, R, and Java.
• Strong software engineering practices applied to semantic and analytics assets: git, pull requests/code review, test/validation practices (e.g., SHACL/dbt tests where applicable), and CI/CD-aware release discipline.
• Excellent problem-solving skills and ability to adapt to new technologies, trends, and frameworks.

Physical Requirements

• Might be in a stationary position for a considerable time (sitting and/or standing).
• Constantly operates a computer.
• Must be able to collaborate with colleagues via conference calls and online meetings.

Pay

$100,000 – $115,000 annually.