Our client is seeking a Senior Consultant – Semantic Data & AI Engineer with 8–12 years of experience to design and deploy knowledge graphs, semantic layers, and AI-driven data solutions. This role combines deep expertise in graph technologies and semantic standards with practical application of modern machine learning and cloud platforms.
Responsibilities & Qualifications
- Design and build knowledge graphs, semantic layers, ontologies, taxonomies, and graph-based data products; translate business concepts into machine-readable semantic models
- Develop end-to-end data pipelines for acquiring, transforming, mapping, validating, and loading information; implement data-quality controls using SHACL validation
- Integrate knowledge graphs with generative AI, RAG/GraphRAG, semantic search, and LLM applications; support NLP and document-intelligence use cases
- Develop Python or Java–based data transformations, APIs, and services; create automated tests and support CI/CD pipelines and production deployments
- Lead technical workstreams, mentor junior consultants, and facilitate requirements and modeling sessions with stakeholders
- Participate in graph-platform evaluations and production deployments; produce technical designs, semantic models, and comprehensive documentation
- Build vector search and semantic search capabilities; demonstrate proficiency in cloud platforms and containerized deployments
Requirements
- 8–12 years of professional experience in data engineering, semantic technologies, or related fields
- Expert-level knowledge of semantic standards and languages: RDF, RDFS, OWL, SPARQL, SHACL, SKOS, JSON-LD, and Turtle
- Hands-on experience with graph databases and platforms: Neo4j, Stardog, GraphDB, Amazon Neptune, Anzo, MarkLogic, TigerGraph, Apache Jena, or TypeDB
- Strong programming skills in Python and Java; proficiency with Git, CI/CD, automated testing, and containerization
- Demonstrated expertise in data pipelines, NLP, machine learning, and vector search technologies
- Experience with cloud platforms: AWS, Azure, Google Cloud, or tools such as Databricks, Snowflake, BigQuery, Redshift, or Microsoft Fabric
- Agile methodology experience and a proven track record of delivering technical solutions in collaborative environments
