Data Modeling Specialist

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.

Key Responsibilities:

• 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.

Required Skills & Experience:

• 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 (PowerCenter, 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., LangChain, LlamaIndex).


• 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.

Preferred Qualifications:

• 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).

Why Join ?

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.