Principal Consultant – Semantic Data & AI Engineering

About the Role

Core Responsibilities

• Design knowledge graphs, semantic layers, ontologies, taxonomies, graph products, and governed machine-readable knowledge models.
• Build pipelines that acquire, transform, map, validate, enrich, and load structured and unstructured data.
• Integrate graphs with generative AI, RAG, GraphRAG, semantic search, intelligent agents, NLP, and document intelligence.
• Develop Python- or Java-based services, APIs, transformations, validation routines, integrations, and automated tests.
• Define data quality, provenance, lineage, confidence, versioning, and governance processes.
• Lead workshops, architecture decisions, prototypes, production implementations, mentoring, proposals, estimates, and client presentations.

What You’ll Bring

• Eight or more years of experience in data engineering, software engineering, artificial intelligence, analytics, enterprise architecture, or a related field.
• At least four years of hands-on knowledge-graph, semantic-technology, graph-database, or semantic-data integration experience.
• Strong knowledge of semantic standards such as RDF, RDFS, OWL, SPARQL, SHACL, SKOS, JSON-LD, Turtle, or related standards.
• Experience with one or more graph platforms and strong programming skills in Python, Java, or a comparable enterprise language.
• Experience developing pipelines, APIs, transformations, automated tests, production integrations, and cloud or modern data-platform solutions.
• Working knowledge of NLP, machine learning, embeddings, vector search, semantic search, RAG, GraphRAG, or LLM applications.
• Ability to communicate with business stakeholders, architects, engineers, data scientists, and executives and take ownership through production delivery.

Preferred Experience

• Financial-services or other regulated-industry experience is strongly preferred.
• Data governance, metadata management, entity resolution, master data, responsible AI, model risk, or regulatory reporting experience is advantageous.
• Relevant cloud, data-engineering, AI/ML, Agile, or graph-technology certifications are a plus.

Technical Scope

• The role may involve relational, graph, document, vector, and lakehouse architectures; batch, streaming, and API-driven pipelines; and cloud platforms such as Azure, AWS, or Google Cloud.
• The role may use platforms including Microsoft Fabric, Databricks, Snowflake, BigQuery, Redshift, Stardog, Neo4j, GraphDB, Amazon Neptune, Anzo, MarkLogic, TigerGraph, Apache Jena, or TypeDB.
• The role includes Git, CI/CD, containers, automated testing, Agile delivery, and production-support practices.

Why Join Capco

• Capco offers work on technology solutions for major financial institutions in a collaborative consulting culture.
• Benefits include medical, dental, vision, 401(k) matching, parental leave, dependent care, tuition reimbursement, wellness reimbursement, HSA, FSA, and commuter benefits.

Recruitment Accessibility

• Capco states that recruitment-process adjustments are available upon request.

Pay Transparency

• The US salary range is $146,000–$183,000 annually.