TigerGraph Developer / Graph Database Engineer

Yotta Systems Inc

Charlotte, NC, United States

9 days ago

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Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Working hours

Regular working hours

Job source

www.dice.com

Tech stack

Java (Programming Language) Amazon Web Services Microsoft Azure Big Data Cloud Computing Data Governance Extract Transform Load (ETL) Database Queries Fraud Prevention and Detection Graph Database Graph Theory Apache Hadoop

+10 more

Python (Programming Language) Machine Learning Neo4j Systems Integration Google Cloud Enterprise Software Applications Apache Spark Apache Kafka Restful APIs Programming Languages

Requirements

Strong hands-on experience developing solutions with TigerGraph.
Strong knowledge of GSQL and TigerGraph query development.
Experience with graph database concepts, graph theory, and graph data modeling.
Experience designing vertices, edges, relationships, and graph schemas for complex enterprise use cases.
Experience developing and optimizing graph queries against large datasets.
Experience with TigerGraph data loading, ingestion, and transformation processes.
Strong SQL skills and experience working with relational data sources.
Experience integrating graph platforms with REST APIs and other enterprise applications.
Experience with Python, Java, or another programming language., * Experience developing graph solutions within banking or financial services is preferred but not required.
Experience with fraud detection, customer/entity relationships, transaction analysis, risk, AML/KYC, cybersecurity, or other graph-oriented financial-services use cases.
Experience with additional graph technologies such as Neo4j, Amazon Neptune, JanusGraph, or similar platforms.
Experience building graph analytics or machine-learning solutions.
Familiarity with graph algorithms including community detection, shortest path, centrality, similarity, and relationship analysis.
Experience with cloud platforms such as AWS, Azure, or Google Cloud.
Experience with Spark, Kafka, Hadoop, or other large-scale data-processing technologies.
Experience working in highly regulated enterprise environments.
Familiarity with enterprise data governance, security, and access-control requirements.