Data Modeling Specialist

Role Overview

We are seeking a Data Modeling Specialist with expertise in knowledge graphs to design and build enterprise-grade data models and semantic layers that translate domain-specific information and metrics into AI-readable formats. This role focuses on enabling an AI-driven reporting system that transforms both structured and unstructured data into insightful monthly reports on key business topics.

Key Responsibilities

• Create and implement comprehensive enterprise data models—including relational, dimensional, and graph-based—that integrate domain-specific entities, KPIs, and evidence into a governed structure readable by AI systems.
• Develop, deploy, and manage knowledge graphs utilizing Neo4j and Cypher to represent complex relationships among business entities, transactions, documents, and evidentiary sources.
• Oversee the entire automatic reporting pipeline covering data ingestion, transformation (ETL/ELT), semantic enrichment, retrieval-augmented generation (RAG), and AI-driven insight generation, culminating in PowerPoint reports populated from templates.
• Build and maintain workflows orchestrating large language model (LLM) retrieval and generation to produce grounded, auditable, and compliant outputs aligned with governance policies.
• Integrate structured data from SQL databases and Informatica tools such as Data Quality, MDM, and Data Governance functions including cataloging and lineage tracking.
• Manage unstructured data like PDFs, emails, and reports by employing object storage solutions such as MinIO or Amazon S3 with metadata tagging, full-text indexing, and semantic retrieval capabilities.
• Collaborate with data stewards, business analysts, and AI/ML engineers to ensure semantic models fit into the enterprise data and AI strategy.

Required Qualifications and Experience

• Practical experience with knowledge graph technologies (Neo4j, Amazon Neptune, Stardog) and query languages such as Cypher and SPARQL.
• Demonstrated skills in developing semantic layers, ontologies, taxonomies, and domain vocabularies for AI and analytics applications.
• Strong proficiency in SQL and experience with Informatica suite components for data integration, quality, metadata management, and governance.
• Experience in building applications powered by LLMs including RAG techniques, prompt design, output auditing, and grounding outputs in data governance.
• Knowledge of AI/ML data pipelines, vector databases like Pinecone and Weaviate, and unstructured data indexing frameworks such as LangChain and LlamaIndex.
• Familiarity with cloud services (AWS, Azure, GCP) and container orchestration tools (Docker, Kubernetes) to support scalable data and AI workflows.
• Understanding of data mesh principles, domain-driven design, and enterprise architecture frameworks like TOGAF is highly advantageous.

Preferred Qualifications

• Master’s degree in Computer Science, Data Science, Information Systems, or related disciplines.
• Certifications in Neo4j, Informatica, cloud platforms (AWS/Azure/GCP), or data governance such as CDMP.

About the Employer

The organization is innovating next-generation AI-native data infrastructure that combines domain knowledge modeling, structured analytics, and generative AI to deliver scalable, actionable business insights.