Data Architect

Responsibilities:

• Design, develop, and maintain data architectures and models specifically leveraging graph database technologies (e.g., Neo4j, Amazon Neptune, TigerGraph).
• 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.

Required Skills and Qualifications:

• 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)
• PowerBI and Databricks knowledge (Nice to 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, TigerGraph, 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.

Preferred:

• 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).