Azure Graph Engineer

Job Description:

Azure Graph Engineer

We are looking for a skilled Graph Data Engineer with expertise in graph engines, graph representation languages, and knowledge/semantic graphs frameworks, as well as working knowledge of Natural Language Processing (NLP), large language models, and machine learning (ML) and deep learning models for classification and clustering. The ideal candidate should have experience with Neo4J and Spark GraphFrames for graph data processing, as well as proficiency in graph representation languages such as OWL and RDF. Knowledge of additional semantic graphs, frameworks and engines like Virtuoso and StarDog would be desirable.

Responsibilities:

• Design, develop, and maintain graph data solutions using Neo4J and/or Spark GraphFrames to meet business requirements.

• Develop and implement efficient graph data models, graph algorithms, and graph queries to extract insights from large-scale graph datasets.

• Optimize graph data pipelines for performance, scalability, and reliability.

• Utilize graph representation languages such as OWL and RDF to define the schema or ontology of the data stored in the graph database.

• Apply working knowledge of NLP, large language models, and ML and deep learning models for classification and clustering tasks.

• Collaborate with data scientists, analysts, and other stakeholders to understand their graph data and NLP/ML requirements and implement appropriate solutions.

• Ensure data quality, data integrity, and data security in all graph data processing and NLP/ML activities.

• Stay updated with the latest advancements in graph data technologies, NLP techniques, and ML frameworks, and provide recommendations for adopting new technologies or techniques to improve graph data processing capabilities.

• Collaborate with cross-functional teams to integrate graph data solutions and NLP/ML models into existing data pipelines or applications.

Requirements:

• Strong expertise in graph engines, particularly Neo4J, with hands-on experience in designing, developing, and optimizing graph data solutions.

• Familiarity with Spark GraphFrames and experience in utilizing it for graph data processing.

• Solid understanding of graph representation languages such as OWL and RDF.

• Knowledge and experience with knowledge/semantic graphs frameworks and engines like Virtuoso and StarDog would be a plus.

• Working knowledge of NLP, large language models, and ML and deep learning models for classification and clustering tasks.

• Proficiency in graph data modelling, graph algorithms, and graph query languages.

• Strong programming skills in languages such as Python, Java, or Scala for graph data processing and NLP/ML tasks.

• Experience with big data technologies such as Hadoop and Spark for large-scale graph data processing.

• Strong problem-solving skills and the ability to work in a fast-paced, collaborative environment.

• Excellent communication skills, both written and verbal, with the ability to communicate technical concepts to both technical and non-technical stakeholders.