REQ: Data and Ontology Engineer in Boston, MA (Onsite)

Hi,

One of our clients is looking for Data and Ontology Engineer in Boston, MA (Onsite)

Title: Data and Ontology Engineer in

Location: Boston, MA (Onsite)

Duration: 8+ Months

C2C or W2 Only

Client is building Energy Intelligence for Services: an AI-driven service that turns existing condition-based maintenance (CBM) analytics into normalized health scores, contextual diagnostics and prioritized action plans for the critical power equipment of data centers, starting with UPS and busway.

The service is developed and validated on historical, already-diagnosed customer data rather than on live connections. A semantic layer - an asset and relationship model built on Company's existing ontology work - gives the diagnostic agents the context they need: which assets are connected, what depends on what, and where they sit on site.

Key Responsibilities:

• Harvest and organise the customer's historical asset, alarm and maintenance data so it can be used for ontology creation.
• Run entity resolution: reconcile the same asset appearing in several systems under several names, and define the identifier strategy (IRIs, named graphs, per-customer and per-site partitioning).
• Build the initial ontology for this dataset on top of the existing client ontology: asset types, power-chain relationships (upstream / downstream, same room, same system) and the links to health-score data.
• Validate the data against the model with SHACL and produce data-quality reports the team can act on.
• Run modelling sessions with service, reliability and CBM experts; turn their knowledge into the model and a shared glossary.
• Treat the ontology and mappings as code: versioned, tested (competency questions as SPARQL tests, SHACL conformance) and run in CI.
• Write the documentation, schema summaries and example queries that ground the diagnostic agents.
• Maintain the competency questions and expected answers used to test the agents on historical incidents.Clearly communicate component status and issues in MS-Office applications e.g. PowerPoint, Excel, Word, Outlook
• Review CAD and 2D drawings for components including GD&T

Mandatory Skills:

• 4+ years building knowledge graphs, ontologies or semantic data platforms that were used in production.
• Hands-on RDF/RDFS, OWL 2, SPARQL 1.1 and SHACL.
• Solid Python (rdflib, pySHACL or similar), git and CI.
• Ability to work with domain experts and to explain modelling choices to software engineers.
• Data preparation and entity resolution on messy, multi-source asset data (relational, spreadsheets, JSON).
• Mapping data to RDF (R2RML/RML or equivalent ETL).

Preferred Requirements:

• Electrical power-chain or data-center domain knowledge (UPS, busway, switchgear, PDUs) and maintenance vocabulary (failure modes, FMEA, condition monitoring).
• Standard vocabularies: Brick, RealEstateCore / ASHRAE 223, SOSA/SSN, QUDT, ISO 14224, IEC 81346.
• Combining knowledge graphs with LLMs: GraphRAG, text-to-SPARQL, ontology-grounded prompting.
• Property graphs (Neo4j/Cypher), with an informed view of when each approach fits.
• Prot g , TopBraid or LinkML used at scale.

Interested candidates, please send your updated resume to: View email address on us.fitly.work

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