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About the Role

Capco is seeking a hands-on Senior Consultant to design and deliver semantic data solutions that make enterprise information usable by artificial intelligence, machine learning, analytics, and business applications. This role is ideal for a versatile consultant who can contribute across knowledge-graph development, AI solution engineering, semantic modeling, and data-pipeline delivery. Depending on project needs, you may work as a knowledge-graph engineer, semantic modeler, AI engineer, data engineer, technical analyst, or workstream lead. You will collaborate with client stakeholders, architects, data scientists, AI engineers, and data engineers to connect structured and unstructured information, create machine-understandable knowledge models, and deliver trusted data foundations for AI. This is a hands-on delivery role requiring participation in modeling, coding, integration, testing, documentation, and production implementation.

Responsibilities

Design and build knowledge graphs, semantic layers, ontologies, taxonomies, and graph-based data products.
Translate business concepts, data models, policies, documents, and subject-matter expertise into machine-readable semantic models.
Develop data pipelines that acquire, transform, map, validate, enrich, and load information from databases, APIs, files, documents, and cloud platforms.
Integrate knowledge graphs with generative AI, retrieval-augmented generation, GraphRAG, semantic search, machine learning, and intelligent-agent solutions.
Support NLP and document-intelligence use cases, including entity extraction, entity linking, relationship extraction, classification, natural language inference, and knowledge extraction.
Combine graph data, metadata, vector search, business rules, and model outputs to improve AI grounding, accuracy, explainability, and traceability.
Develop Python- or Java-based data transformations, APIs, services, validation routines, and integration components.
Prepare and manage data used for AI retrieval, model evaluation, inference, and analytics.
Implement semantic-data quality controls, including SHACL validation, provenance, lineage, confidence scoring, and version management.
Participate in graph-platform evaluations, proofs of concept, architecture decisions, performance testing, and production deployments.
Create automated tests and support CI/CD, monitoring, troubleshooting, and production-support activities.
Facilitate requirements and modeling sessions with business and technical stakeholders.
Produce technical designs, semantic models, mappings, test cases, deployment documentation, and operational procedures.
Lead defined technical workstreams and mentor junior consultants, engineers, and analysts.
Contribute to reusable solution patterns, demonstrations, accelerators, proposals, and client presentations.

Requirements

Four to six years of experience in data engineering, software engineering, artificial intelligence, analytics, knowledge management, or a related technology discipline.
Two or more years of hands-on experience with knowledge graphs, semantic technologies, graph databases, semantic-data integration, or closely related solutions.
Working knowledge of semantic standards such as RDF, RDFS, OWL, SPARQL, SHACL, SKOS, JSON-LD, or Turtle.
Experience with at least one graph platform such as Stardog, Neo4j, GraphDB, Amazon Neptune, Anzo, MarkLogic, TigerGraph, Apache Jena, TypeDB, or an equivalent technology.
Proficiency in Python, Java, or another enterprise programming language.
Experience developing data pipelines, transformations, APIs, automated tests, or production integrations.
Working knowledge of NLP, machine learning, embeddings, vector search, semantic search, RAG, GraphRAG, or LLM-based applications.
Experience integrating structured data with unstructured content such as policies, contracts, research, communications, or operational documents.
Familiarity with one or more cloud or modern data platforms, including Microsoft Azure, AWS, Google Cloud, Microsoft Fabric, Databricks, Snowflake, BigQuery, or Redshift.
Understanding of relational, graph, document, vector, and lakehouse data architectures.
Familiarity with Git, CI/CD, automated testing, containers, Agile delivery, and production-support practices.
Strong analytical, problem-solving, documentation, and communication skills.
Ability to work across multiple technical roles, learn unfamiliar technologies, and contribute throughout the delivery lifecycle.
Experience in financial services or another regulated industry is preferred.
Familiarity with data governance, metadata management, entity resolution, master data, responsible AI, model risk, regulatory reporting, or data privacy is advantageous.
A bachelor’s degree or equivalent professional experience in computer science, data science, information systems, engineering, linguistics, mathematics, or a related discipline is preferred.
Relevant cloud, data-engineering, AI/ML, Agile, or graph-technology certifications are a plus.

Skills

Knowledge Graphs
Semantic Technologies
Graph Databases
Semantic Data Integration
RDF
RDFS
OWL
SPARQL
SHACL
SKOS
JSON-LD
Turtle
Stardog
Neo4j
GraphDB
Amazon Neptune
Anzo
MarkLogic
TigerGraph
Apache Jena
TypeDB
Python
Java
Data Pipelines
APIs
Automated Tests
Production Integrations
NLP
Machine Learning
Embeddings
Vector Search
Semantic Search
RAG
GraphRAG
LLM
Generative AI
Retrieval-Augmented Generation
Intelligent Agents
Document Intelligence
Entity Extraction
Entity Linking
Relationship Extraction
Classification
Natural Language Inference
Knowledge Extraction
Graph Data
Metadata
Business Rules
AI Grounding
AI Accuracy
AI Explainability
AI Traceability
Data Quality Controls
Provenance
Lineage
Confidence Scoring
Version Management
Graph Platform Evaluation
Proof of Concept
Architecture Decisions
Performance Testing
Production Deployments
Automated Testing
CI/CD
Monitoring
Troubleshooting
Production Support
Requirements Facilitation
Modeling Sessions
Technical Designs
Semantic Models
Mappings
Test Cases
Deployment Documentation
Operational Procedures
Workstream Leadership
Mentoring
Solution Patterns
Demonstrations
Accelerators
Proposals
Client Presentations
Financial Services
Data Governance
Metadata Management
Entity Resolution
Master Data
Responsible AI
Model Risk
Regulatory Reporting
Data Privacy
Computer Science
Data Science
Information Systems
Engineering
Linguistics
Mathematics
Cloud Platforms
Microsoft Azure
AWS
Google Cloud
Microsoft Fabric
Databricks
Snowflake
BigQuery
Redshift
Relational Databases
Document Databases
Vector Databases
Lakehouse Architectures
Git
Agile Delivery
Analytical Skills
Problem-Solving Skills
Documentation Skills
Communication Skills
Cloud Certifications
Data Engineering Certifications
AI/ML Certifications
Agile Certifications
Graph Technology Certifications

Location

New York, NY

Work Type

Hybrid

Experience Level

Senior
Four to six years
Two or more years

Education Level

Bachelor's degree or equivalent professional experience

Salary/Compensations

$114,000—$143,000 USD

Benefits

Medical, Dental and Vision
401k match
Maternity and paternity leave and dependent care
Tuition reimbursement and wellness reimbursement
Working Advantage (discounted marketplace), HSA, FSA, and commuter benefits

About the Company

Capco is seeking a hands-on Senior Consultant to design and deliver semantic data solutions that make enterprise information usable by artificial intelligence, machine learning, analytics, and business applications.
Deliver high-impact technology solutions for Tier 1 financial institutions.
Work in a collaborative, flat, and entrepreneurial consulting culture.
Access continuous learning, training, and industry certifications.
Be part of a team shaping the future of digital financial services.
Help shape the future of digital transformation across FS & Energy.

Equal Opportunity

We’re committed to making our recruitment process accessible and straightforward for everyone. If you need any adjustments at any stage, just let us know – we’ll be happy to help. We value each person’s unique perspective and contribution. At Capco, we believe that being yourself is your greatest strength. Our #BeYourselfAtWork culture encourages individuality and collaboration – a mindset that shapes how we work with clients and each other every day.