We are seeking an experienced AI Engineer with strong expertise in Graph Databases (Neo4j or Amazon Neptune), Metadata Modelling, and Enterprise Data Architecture. This role will focus on building intelligent data discovery, knowledge graph, lineage, and AI-powered solutions capable of understanding complex data relationships across large-scale enterprise environments.

The ideal candidate will have experience developing Knowledge Graphs, implementing Graph-based AI solutions, and designing metadata-driven architectures to support advanced analytics, data governance, lineage, and generative AI use cases. Key Responsibilities

Design, develop, and maintain enterprise-scale Knowledge Graphs using Neo4j or Amazon Neptune.

Develop AI-powered solutions leveraging graph relationships, metadata, and semantic models.

Build and maintain metadata repositories, taxonomies, ontologies, and business glossaries.

Model complex enterprise datasets and relationships spanning multiple platforms and integration points.

Design graph schemas to support data lineage, impact analysis, governance, and AI-driven discovery.

Implement Retrieval-Augmented Generation (RAG) and Knowledge Graph-based AI capabilities.

Collaborate with Data Engineers, Architects, Data Governance teams,



and Business Stakeholders to define metadata and graph modelling standards.

Create and maintain end-to-end data lineage mappings across source systems, transformation layers, and consumption platforms.

Develop APIs, graph queries, and services supporting AI and data platform initiatives.

Drive best practices around metadata management, semantic modelling, and enterprise information architecture.

Required Skills & Experience

7+ years of experience in Data Engineering, AI Engineering, or Data Architecture.

Strong hands-on experience with Neo4j and/or Amazon Neptune.

Proven experience building and maintaining Knowledge Graphs within large enterprise environments.

Robust understanding of:Graph Data Modelling

Property Graphs

RDF

Ontologies

Taxonomies

Semantic Data Models

Hands-on experience in Metadata Modelling and Metadata Management Frameworks.

Experience implementing Data Lineage, Impact Analysis, and Data Discovery solutions.

Strong programming skills in Python, Java, or Scala.

Experience with graph query languages such as:Cypher

Gremlin

SPARQL

Experience integrating graph databases with AI/ML and Generative AI solutions.

Strong understanding of enterprise data ecosystems and integration architectures.

📌 Data Scientist (Graph DB) (Sydney)
🏢 Synechron
📍 Sydney