3 months ago
Base Salary
$146k - $183k/yr
Responsibilities
- Design and implement enterprise knowledge graphs, semantic layers, ontologies, taxonomies, and graph-based data products.
- Translate business concepts, policies, documents, data models, and subject-matter expertise into governed, machine-readable knowledge models.
- Build pipelines that acquire, transform, map, validate, enrich, and load structured and unstructured data from databases, APIs, files, documents, events, and cloud platforms.
- Integrate knowledge graphs with generative AI, machine learning, retrieval-augmented generation, GraphRAG, semantic search, and intelligent-agent solutions.
- Develop Python- or Java-based services, data transformations, APIs, validation routines, automated tests, and production integrations.
- Support NLP and document-intelligence use cases including entity extraction, entity linking, relationship extraction, classification, natural language inference, and knowledge extraction.
- Define semantic-data quality controls, provenance, lineage, confidence scoring, versioning, and governance processes.
- Evaluate graph databases, vector databases, data platforms, AI frameworks, and cloud services for client requirements.
- Lead technical workshops, architecture decisions, prototypes, and production implementations.
- Mentor team members, create reusable technical patterns and reference architectures, and support proposals, estimates, client presentations, and consulting offerings.
Requirements
- At least eight years of experience in data engineering, software engineering, artificial intelligence, analytics, enterprise architecture, or a related field.
- At least four years of hands-on experience with knowledge graphs, semantic technologies, graph databases, or semantic-data integration.
- Strong knowledge of RDF, RDFS, OWL, SPARQL, SHACL, SKOS, JSON-LD, Turtle, or related standards.
- Experience with one or more graph platforms such as Stardog, Neo4j, GraphDB, Amazon Neptune, Anzo, MarkLogic, TigerGraph, Apache Jena, or TypeDB.
- Strong programming skills in Python, Java, or a comparable enterprise language.
- Experience developing data pipelines, APIs, transformations, automated tests, and production integrations.
- Working knowledge of machine learning, embeddings, vector search, semantic search, RAG, GraphRAG, or LLM-based applications.
- Experience connecting structured data with unstructured content such as policies, contracts, research, communications, or operational documents.
- Familiarity with Microsoft Azure, AWS, Google Cloud, Microsoft Fabric, Databricks, Snowflake, BigQuery, or Redshift.
- Understanding of relational, graph, document, vector, and lakehouse architectures and their appropriate use cases.
- Experience with Git, automated testing, containers, and production-support practices.
- Ability to communicate technical concepts to business stakeholders, architects, engineers, data scientists, and executives, and take ownership from discovery through production delivery.
- Financial-services or other regulated-industry experience is strongly preferred.
- Experience with data governance, metadata management, entity resolution, master data, responsible AI, model risk, or regulatory reporting is advantageous.
- Relevant cloud, data-engineering, AI/ML, Agile, or graph-technology certifications are preferred.
Benefits
- Medical, dental, and vision coverage.
- 401(k) match.
- Maternity and paternity leave and dependent care benefits.
- Tuition reimbursement and wellness reimbursement.
- Working Advantage discounted marketplace, HSA, FSA, and commuter benefits.
- Access to continuous learning, training, and industry certifications.
- New York, NY role with a hybrid work arrangement indicated by the posting.
Tech Stack
Categories
BackendData Engineering
About Capco
Capco is a global technology and management consultancy focused on financial services, helping banks, capital markets, insurance, and wealth firms with digital transformation, risk and compliance, and data/AI-enabled modernization. Founded in 1998 and headquartered in London, it operates as a Wipro company. Its business model centers on project-based consulting, managed services, and solution delivery across strategy, engineering, and platforms for regulated institutions.