Data Modeling Specialist Job ID: 383450

Role:
Data Modeler & Knowledge Graph Specialist
– Design and implement enterprise-grade data models, semantic layers, and knowledge graphs that make domain-specific entities, metrics, and supporting evidence machine-readable. Enable an AI-driven reporting pipeline that transforms unstructured and structured data into monthly, template-based insight reports on strategic business topics.

• Design and implement enterprise data models (relational, dimensional, and graph-based) that unify domain-specific entities, KPIs, metrics, and supporting evidence into an AI-readable, governed structure.
• Design, develop, and deploy knowledge graphs using Neo4j and Cypher to model complex relationships between business entities, transactions, documents, and evidence sources.
• Own end-to-end automated reporting pipeline – from data ingestion and transformation (ETL/ELT), semantic enrichment, retrieval-augmented generation (RAG), to AI-generated insights and populated PowerPoint deliverables using predefined templates.
• Build and maintain LLM orchestration workflows for retrieval and generation, ensuring grounded, auditable, and compliant outputs aligned with business governance policies.
• Integrate structured data sources using SQL
  , Informatica Data Quality (IDQ),
  Informatica MDM
  , and Data Governance practices for cataloging, lineage, and quality.
• Organize and govern unstructured data (PDFs, emails, reports, etc.) using MinIO
  , Amazon S3
  , or S3-compatible object storage with metadata tagging, full-text indexing, and semantic retrieval support.
• Collaborate with data stewards, business analysts, and AI/ML engineers to align semantic models with enterprise data strategy and AI roadmap.

• Hands-on experience with knowledge graph platforms (e.g.,
  Neo4j
  , Amazon Neptune
  , Stardog
  ) and query languages (
  Cypher
  , SPARQL).
• Proven experience developing semantic layers
  , ontologies
  , taxonomies
  , and domain-specific vocabularies for AI and analytics use cases.
• Strong SQL skills and experience with Informatica suite (Power Center, IDQ, MDM, Data Catalog) for data integration
  , data quality
  , metadata management
  , and data governance
  .
• Experience building LLM-powered applications
  , including Retrieval-Augmented Generation (RAG), prompt engineering, output validation, and grounding AI narratives in governed data.
• Familiarity with AI/ML data pipelines
  , vector databases (e.g., Pinecone, Weaviate), and unstructured data indexing/retrieval frameworks (e.g., Lang Chain, Llama Index).
• Experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes) for scalable data engineering and AI workflows.
• Understanding of data mesh
  , domain-driven design (DDD), and enterprise architecture frameworks (e.g., TOGAF) is a strong plus.

• Master’s degree in Computer Science, Data Science, Information Systems, or related field.
• Certifications in Neo4j
  , Informatica
  , AWS/Azure/GCP
  , or data governance (e.g., CDMP).

Our client is building the next generation of AI-native data infrastructure—where domain knowledge, structured analytics, and generative AI converge to deliver actionable business insight at scale.