Professional Resume Template for

Knowledge Engineer

Dorian S. Hayes

San Jose, CA

(408) 555-0174

dorian.hayes@email.com

linkedin.com/in/dorian-hayes | github.com/dorianhayes | dorianhayes.dev

Professional Summary

Systems-oriented Knowledge Engineer with 5 years of experience designing and implementing enterprise knowledge graphs, semantic search architectures, and structured taxonomies. Proven expertise in engineering ontology models, building retrieval-augmented generation pipelines, and developing SPARQL query scripts for graph databases. Successfully optimized search relevance by 26% and reduced internal documentation retrieval time by 32% across 3 enterprise-scale data integration projects. Proficient with Neo4j, Apache Jena, SPARQL, Python, RDF/OWL, and Elasticsearch, with a strong background in natural language processing and semantic web standards.

Work Experience

Knowledge Engineer — Syntactic Technologies

San Jose, CA | July 2023 – Present

  • Architected and deployed an enterprise knowledge graph using Neo4j to link 150,000+ data nodes, reducing cross-departmental data retrieval time by 34% and streamlining information retrieval.
  • Designed 8 custom taxonomy schemas and ontology models to classify unstructured document repositories, boosting search precision by 28% and decreasing manual tagging errors.
  • Constructed semantic mapping algorithms using Python and RDF/XML, which converted 4 legacy data silos into a unified graph format, saving 18 hours of weekly data engineering work.
  • Collaborated with AI engineers to build a retrieval-augmented generation (RAG) system utilizing semantic search, improving internal answer generation accuracy by 22% overall.

Associate Knowledge Engineer — Cognitive Data Labs

Palo Alto, CA | June 2021 – June 2023

  • Maintained and updated a corporate knowledge base containing 85,000+ support articles, decreasing search query abandonment rates by 19% through metadata enrichment.
  • Conducted weekly data audits on 12 distinct database schemas, identifying and correcting semantic inconsistencies to improve knowledge graph integration reliability by 24%.
  • Authored 14 detailed ontology governance documents and metadata schema manuals, which reduced the onboarding time of incoming information specialists by 3 weeks.
  • Wrote custom SPARQL query scripts and Python ETL jobs to import 5,000+ new terminology terms into the central graph database, expanding semantic coverage by 15%.

Education

Bachelor of Science in Cognitive Science

San Jose State University · San Jose, CA · 2021

Skills

Knowledge Graphs, Ontology Engineering, Taxonomy Design, Semantic Web, SPARQL, Neo4j, Apache Jena, RDF/OWL, Python, SQL, Elasticsearch, Natural Language Processing, RAG Systems, Metadata Schema, Information Extraction, Vector Databases, Git

Projects

Semantic RAG Pipeline Optimization

Role: Lead Knowledge Engineer

Tools: Neo4j, Python, OpenAI API, LangChain

Engineered a hybrid semantic-vector search pipeline linking 40,000+ data nodes, reducing system hallucination rates by 35% and improving question-answering accuracy.

Legacy Taxonomy Migration

Role: Knowledge Engineer

Tools: PoolParty, SPARQL, Python, Apache Jena

Successfully migrated 3 legacy classification taxonomies containing 6,500+ terms into a unified ontology, resolving 92% of cross-repository metadata conflicts.

Certifications

  • Certified Knowledge Manager (CKM) (2023)
  • Neo4j Certified Professional (2022)

Additional information

  • Languages: English (Native), French (Conversational)
  • Volunteer Work: Taxonomy curator for open-source digital heritage archive (2022-present)
  • Availability: 2 weeks notice

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Job Market Insights

Market data and opportunities for

Knowledge Engineer

Job Market Insights

$88,000

-

$135,000

Avg:

$110,000

Growth Outlook:

The demand for Knowledge Engineers in the United States is rising rapidly, fueled by the growth of artificial intelligence and graph databases. As enterprises build advanced AI applications, structuring unstructured corporate data using taxonomies and ontologies has become critical to preventing model hallucinations. Consequently, companies in tech, finance, and healthcare are actively recruiting experts who can bridge the gap between human language and structured logical data. Job openings are projected to grow by 14% over the next decade.

14% growth over 10 years

Key Skills Required

Focus on these skills when customizing your resume for recruiter screenings.

Designing, extending, and maintaining enterprise-wide taxonomy and ontology models using standard semantic web technologies like RDF, OWL, and triple stores. || Engineering robust knowledge graph solutions using graph databases such as Neo4j or Amazon Neptune, including writing optimized SPARQL or Cypher query scripts. || Collaborating with machine learning and data engineering teams to build and scale semantic search, information extraction, and retrieval-augmented generation systems.

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Knowledge Engineer

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