Graph Database Developer

·      Build Graph Database solutions leveraging large-scale datasets to solve various business use cases.

·      Design and build graph data models to support variety of use cases including knowledge graphs

·      Design and build graph database load processes to efficiently populate the graph database

·       Strong organizational skills, with the ability to work autonomously as well as in a team-based environment

·      Data pipeline framework development

 

The candidate must demonstrate proficiency in,

·      Solid understanding of graph data modeling, graph schema development, graph data design.

·      Graph data modeling (Experience with graph data models) and graph languages (Cypher, Gremlin, SparQL), exposure to various graph data modeling techniques)

·      Candidate should have hands-on experience with Neo4j database and the Cypher query language.

·      Candidate should know basic network science concepts and graph algorithms.

·      Candidate should be able to write efficient & accurate Cypher queries to solve business problems.

·      Candidate should have a strong understanding of how graph data looks like and how it can be created from relational data.

·      Candidate should be able import data into Neo4j effectively and handle Neo4j database instances.

·      Fluency in complex SQL and experience with RDBMSs.

·      Project Experience in Python, Spark, PySpark, Scala, Python, NiFi, Hive, NoSql DBs.

·      Deep understanding of representing relational models using a graph data base for large clusters of nodes.

·      Relevant experience in general data base design with emphasis on graph storage models.

·      Should be able to write efficient & accurate Cypher queries to solve business problems.

·      Experience working on any Databricks would be added advantage.

·      Solid grounding in Agile methodologies.

·      Experience with git and other source control systems.

 

·      Neo4j Certified Developer Certification.

·      Design and build graph data models to support variety of use cases including knowledge graphs.

·      Strong delivery background across the delivery of high-value, business-facing technical projects in major organizations.

·      Experience of managing client delivery teams, ideally coming from a Data Engineering / Data Science environment.