Anblicks
Graph Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Graph Engineer with 8+ years in Data Engineering or Software Development, 2+ years in Knowledge Graph development. Requires expertise in graph databases, Python, data pipelines, and cloud platforms. Contract length and pay rate are unspecified.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
February 13, 2026
🕒 - Duration
Unknown
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🏝️ - Location
Unknown
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
Dallas, TX
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🧠 - Skills detailed
#GIT #Scala #Neo4J #Python #Data Engineering #TigerGraph #Spark (Apache Spark) #MDM (Master Data Management) #Data Modeling #DevOps #Data Pipeline #dbt (data build tool) #Apache Spark #Knowledge Graph #RDF (Resource Description Framework) #Cloud #Version Control #AWS (Amazon Web Services) #Airflow #Programming #"ETL (Extract #Transform #Load)" #Databases #Data Manipulation #Graph Databases #Data Management #Data Transformations #Kafka (Apache Kafka) #Azure
Role description
Experience
• 8+ years of hands-on technical experience in Data Engineering, Software Development, or Analytics.
• 2+ years dedicated hands-on experience in Knowledge Graph development and relationship mapping, preferably with customer or client data.
Technical Skills
• Knowledge Graph/Ontology: Deep practical expertise in graph data modeling, ontology development, and semantic modeling principles (RDF, RDFS, OWL, SHACL).
• Graph Databases: Proven hands-on experience with at least one major Graph Database technology such as Neo4j, AWS Neptune, TigerGraph, or JanusGraph, and expertise in native query languages (Cypher, SPARQL, or Gremlin).
• Graph Analytics: Strong experience with graph algorithms including community detection, centrality measures, path finding, pattern matching, and relationship scoring.
• Programming: Strong proficiency in Python for data manipulation, graph algorithm implementation, and data transformations.
• Data Engineering: Solid experience building scalable data pipelines using modern tools such as Apache Spark, Kafka, Airflow, or dbt.
• Customer Data: Understanding of customer master data management, and entity resolution techniques.
• Cloud & DevOps: Experience with version control (Git) and familiarity with CI/CD processes and major cloud platforms (AWS, Azure).
Experience
• 8+ years of hands-on technical experience in Data Engineering, Software Development, or Analytics.
• 2+ years dedicated hands-on experience in Knowledge Graph development and relationship mapping, preferably with customer or client data.
Technical Skills
• Knowledge Graph/Ontology: Deep practical expertise in graph data modeling, ontology development, and semantic modeling principles (RDF, RDFS, OWL, SHACL).
• Graph Databases: Proven hands-on experience with at least one major Graph Database technology such as Neo4j, AWS Neptune, TigerGraph, or JanusGraph, and expertise in native query languages (Cypher, SPARQL, or Gremlin).
• Graph Analytics: Strong experience with graph algorithms including community detection, centrality measures, path finding, pattern matching, and relationship scoring.
• Programming: Strong proficiency in Python for data manipulation, graph algorithm implementation, and data transformations.
• Data Engineering: Solid experience building scalable data pipelines using modern tools such as Apache Spark, Kafka, Airflow, or dbt.
• Customer Data: Understanding of customer master data management, and entity resolution techniques.
• Cloud & DevOps: Experience with version control (Git) and familiarity with CI/CD processes and major cloud platforms (AWS, Azure).
