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 ResponsibilitiesDesign 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 & ExperienceHands-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 QualificationsMaster’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.Skills: sql,neo4j,cypher