GraphQL Data Engineer

Role Sr. Knowledge graph & Data engineer. Experienced professional with a strong focus on Labelled Property Graph (LPG) and proficiency in data engineering. If you have a solid background in computer science, data analytics, and LPG technologies such as Neo4j and LPG Query languages such as Cypher/Open Cypher Proven experience as a Knowledge Engineer, Data Engineer, or a similar role, with a strong focus on LPG and data engineering. Proficient in data engineering tools and technologies, such as Python, SQL, Spark, Hadoop, and ETL / ELT frameworks. Deep understanding of LPG concepts and technologies. Designing, developing, and deploying customised and scalable knowledge graph solutions or products. Deep knowledge in Graph Query Languages (Cypher/Open Cypher, Gremlin). Data/Software Engineering proficiency with Object-Oriented Programming Languages (e.g., Java, Python, C++) and/or Dynamic Programming Languages (e.g., Python, Perl). Working knowledge of a range of database technologies including RDBMS, NoSQL. Experience with data analytics techniques. Object Graph Mapping libraries and/or Aspect Oriented Programming. Data engineering using modern data platforms to build, deploy, and maintain data applications. Application deployment technologies (containerised workflows, Kubernetes) and cloud provisioning tools (CloudFormation, Terraform). Familiarity with AWS would be advantageous. Web-services development and consumption (e.g., RESTFul, GraphQL). Graph visualization technologies and tools (e.g., Neo4j Bloom, SigmaJS, Gephi). Full text search and indexing (e.g., Solr/Lucene, Elastic Search). Experience with Django, Docusaurus, and React would be advantageous. Experience with machine learning and AI algorithms. Familiarity with cloud computing platforms, such as AWS, Azure, or Google Cloud Platform. Experience with big data technologies, such as Hadoop, Spark, or Flink. Experience working in an Agile development environment.