What are the responsibilities and job description for the Neo4J /Graph DB Architect position at InfiCare Inc?
Neo4J Sr Architect
Location: Remote
Long Term role
Key Responsibilities:
• Lead the design, development, and deployment of Neo4j/GraphDB solutions.
• Define graph database models and optimize queries for performance and scalability.
• Implement data pipelines and ETL processes for integrating graph databases with enterprise systems.
• Develop custom procedures, algorithms, and indexing strategies to optimize graph search capabilities.
• Monitor database health, troubleshoot performance issues, and implement optimizations.
• Collaborate with cross-functional teams including data engineers, software developers, and data scientists.
• Define best practices for graph database security, data governance, and access control.
• Stay updated with the latest advancements in GraphDB technologies and propose innovative solutions.
• Mentor junior engineers and drive team competency in graph database development.
Required Skills & Experience:
• 8 years of experience in database engineering, with at least 4 years of hands-on experience in Neo4j/GraphDB.
• Expertise in Cypher query language and performance tuning of graph queries.
• Experience with Graph algorithms, RDF, SPARQL, and property graphs.
• Strong knowledge of data modeling, indexing, and schema design for graph databases.
• Proficiency in Python, Java, or other programming languages for database interactions.
• Hands-on experience with ETL tools and data pipeline frameworks.
• Experience in deploying graph databases on cloud platforms (AWS, Azure, GCP).
• Knowledge of security best practices in GraphDB implementations.
• Strong problem-solving skills and ability to lead a technical team effectively.
Preferred Qualifications:
• Experience with Apache TinkerPop/Gremlin, ArangoDB, TigerGraph, or similar graph database technologies.
• Experience with AI/ML-driven graph analytics.
• Familiarity with containerization (Docker, Kubernetes) and CI/CD pipelines.
• Knowledge of big data processing frameworks (Spark, Kafka, etc.).
