Information Technology_USA - USA_Engineer

Real Soft•Jacksonville, FL

5d•Hybrid

About The Position

We are seeking an experienced Data Architect / Engineer with expertise in Graph DB experience and ideally knowledge of Graph RAG patterns and Ontology including OWL to join our team and support on the development and implementation of a knowledge repository platform. In this role, you will design, build, and optimize data architectures that enable robust, scalable, and efficient knowledge of representation and discovery across complex, interconnected datasets.

Requirements

Proven experience as a Data Architect, Data Engineer, or in a similar role with a focus on graph databases.
Experience with .NET development. (Must have)
Exposure to Azure DevOps.
Hands-on experience designing and deploying knowledge graphs and graph data models.
Strong proficiency in graph query languages such as Cypher, Gremlin, or SPARQL.
In-depth knowledge of graph database platforms (Neo4j, Amazon Neptune, Tiger Graph, etc.).
Solid understanding of data modeling concepts, relational and NoSQL databases.
Experience designing ETL pipelines and data workflows for graph-based systems.
Proficiency in programming languages such as Python, Java, or Scala used for data processing.
Familiarity with cloud platforms and services (AWS, Azure, GCP) relevant to data architecture.
Understanding of data governance, metadata management, and security protocols.
Excellent problem-solving skills and ability to work collaboratively in cross-functional teams.
Strong communication skills to convey technical concepts to both technical and non-technical stakeholders.
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Nice To Haves

Power BI and Databricks knowledge
Experience with Semantic Web technologies and standards (RDF, OWL, Linked Data).
Knowledge of AI/ML applications leveraging graph data.
Background in knowledge management, knowledge graphs, or ontologies.
Familiarity with containerization and orchestration tools (Docker, Kubernetes).

Responsibilities

Design, develop, and maintain data architectures and models specifically leveraging graph database technologies (e.g., Neo4j, Amazon Neptune, Tiger Graph).
Collaborate with data scientists, data engineers, and domain experts to understand data requirements and translate them into scalable graph data models and solutions.
Develop ETL/ELT processes for ingesting, transforming, and loading data into graph databases, ensuring data integrity, quality, and consistency.
Optimize data storage and retrieval for performance, query efficiency, and scalability in graph environments.
Implement data governance and security best practices in accordance with organizational policies.
Analyze complex datasets to identify relationships and create knowledge graphs that support insights and innovation.
Ensure seamless integration with other data platforms, APIs, and services within the overall data ecosystem.
Provide technical leadership, documentation, and standards for graph data architecture.
Stay updated with the latest trends and advancements in graph technology and data architecture.

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