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Virtusa
Bachelors or masters degree in computer science, data science, engineering, or a related field.
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.
Solid understanding of computer science fundamentals.
Excellent problem-solving, analytical, and critical thinking skills.
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.
Programming languages that combine object-oriented and functional programming (e.g., Scala).
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.
In addition, candidates will be expected to demonstrate:
Previous engagement with business stakeholders to deliver successful data engineering projects.
Excellent communication and facilitation skills, with the ability to effectively collaborate with cross-functional teams and present complex information to both technical and non-technical audiences.
Good written and verbal skills, fluent English.
Be creative, collaborative, and product focused.
Good at time and priority management with the ability to work in a challenging and multi-cultural international environment, as well as to work independently and collaboratively in a highly interdisciplinary environment
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