Knowledge Graph Engineer
vor 4 Wochen
Your Role
You will play a crucial role in shaping the future of Data & Analytics and actively contribute to the success of the digital transformation at ZEISS. Within the Enterprise Data Management Team of our rapidly growing Data & Analytics organisation, you will help our business units to design, build, and maintain knowledge-based systems, driven by the vision to enable everyone to effectively find, learn, share, & innovate throughout the enterprise.
You will
- Integrate information into knowledge-graph based systems and engage in data & knowledge / ontology modelling, knowledge graph construction, and validation
- Develop and apply algorithms based on graph queries / analytics (e.g., SPARQL), graph reasoning (e.g., RDFS+, OWL), AI/ML (e.g., NLP, graph embeddings) to enable various analytics use cases leveraging knowledge graphs
- Work in a team with data scientists, data & software engineers & product owners to create scalable, reusable and performant data-oriented applications, incl. e.g., chatbots, recommender, search, and other knowledge-based systems
- Convey technically difficult concepts in a clear and understandable way, translate business needs to technical specifications, and provide guidance for knowledge graph & ontology development to other teams
- Evaluate the latest methods and technologies and support the design of our data & analytics platforms and governance infrastructures - Continuously improve quality and performance while owning applications from idea to operations
Your profile
- An excellent university degree (MSc/PhD) in information technology, computer science, natural sciences, or similar training
- At least 3 years of working experience in data integration, building (semantic) knowledge graphs, querying (graph) data using standard query languages (SQL, SPARQL)
- Familiarity with machine actionable languages (e.g., RDF), linked data principles and standards, & OWL-based ontology modelling in commonly used tools
- Excellent programming skills in Python, including mastering the standard libraries for NLP, machine learning and data science; knowledge of at least one other programming language (e.g. Java, Javascript) is a plus
- Solid understanding of at least one of Graph Analytics, Machine Learning / Deep Learning, Natural Language Processing
- An independent (“can-do”), solution-oriented and team-oriented way of working, not afraid to take on responsibility
- Strong desire to learn & upskill at the intersection of data, science & industry
- Experience with the following is welcome and considered as a plus: Cloud technologies like Microsoft Azure (e.g., Synapse, Databricks, Azure DevOps) - CI/CD using e.g., git, docker - Agile software-development using Scrum / Kanban
Your ZEISS Recruiting Team:
Annett Burger, Markus Repp
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