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CLPS Global · 1 day ago

Data Engineer

New Jersey, United States

Full-time

Onsite

Mid Level

CLPS Global is a technology and consulting firm specializing in digital transformation solutions. They are seeking a Data Engineer with expertise in Neo4j Graph to work on meaningful projects, collaborate with colleagues, and contribute to the company's success.

ConsultingInformation ServicesInformation TechnologyInsurance

Hiring Manager

swathy s

Responsibilities

A Neo4j graph ontology skill set profile involves modeling skills as a graph database where skills, roles, and people are nodes and relationships are the connections between them

Cypher: This is Neo4j's native graph query language. The ability to write and understand Cypher is essential for querying the graph to find relationships and patterns in skills

Graph Data Modeling: Understanding how to model complex relationships in a graph is fundamental. This includes defining node labels (e.g., Person, Skill, JobRole) and relationship types (e.g., HAS_SKILL, REQUIRES_SKILL, WORKS_ON)

Ontology Design: This involves formally defining the domain model, including the types of entities, their properties, and the relationships between them. This provides a structured framework for building the graph and ensuring consistency

Query Profiling: A key skill is the ability to profile query execution to identify bottlenecks and optimize performance, often by adding PROFILE to a Cypher query to see the execution plan

Integration: Proficiency in languages like Python is valuable for writing scripts to load data into the graph, build the graph based on the ontology, and integrate Neo4j with other systems

Skill ontology engineering: This is the specific application of ontology design to the skill domain, focusing on creating a formal and dynamic model for skills, their adjacencies, and their relationships to roles and projects

Knowledge Graph Construction: The overall process of building a knowledge graph from raw data, guided by the ontology, is a key skill

Graph algorithms: The ability to apply algorithms (e.g., shortest path, community detection) to the graph can uncover deeper insights into skill relationships and talent pools

AI/ML integration: Leveraging the skill ontology to train AI/ML models for tasks like resume screening, job matching, and skills gap analysis is an increasingly important skill

Data Governance and Security: Applying ontology reasoning to check the consistency of security rules applied to the graph database is a specific and valuable skill

Qualification

CypherGraph Data ModelingOntology DesignQuery ProfilingIntegrationSkill Ontology EngineeringKnowledge Graph ConstructionGraph AlgorithmsAI/ML IntegrationData GovernanceSecurity

Required

Ability to write and understand Cypher for querying the graph

Understanding how to model complex relationships in a graph

Ability to define node labels and relationship types

Formally defining the domain model including types of entities, their properties, and relationships

Ability to profile query execution to identify bottlenecks and optimize performance

Proficiency in languages like Python for writing scripts to load data into the graph

Skill ontology engineering focusing on creating a formal and dynamic model for skills

Knowledge graph construction from raw data guided by the ontology

Ability to apply graph algorithms to uncover deeper insights into skill relationships

Leveraging skill ontology to train AI/ML models for tasks like resume screening

Applying ontology reasoning to check the consistency of security rules applied to the graph database

Company

CLPS Global

CLPS Incorporation (NASDAQ: CLPS), established in 2005 and headquartered in Hong Kong, is at the forefront of driving digital transformation and optimizing operational efficiency across industries through innovations in artificial intelligence, cloud computing, and big data.

Founded in 2005