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(Senior) Data Engineer: RDF Knowledge Graphs and Generative AI(m/w/x)
Building RDF Knowledge Graphs and Generative AI data pipelines for SAP. Mapping source data into ontologies and operating triple stores in production. PhD or Master's degree in CS, AI, physics, or math required.
Requirements
- PhD or Master’s degree in computer science, AI, physics, or mathematics
- 2+ years professional experience in Data Engineering
- Experience with Knowledge Graphs in business context
- Designing and operating large-scale data pipelines
- Deep working proficiency in RDF Knowledge Graph stack
- Hands-on experience operating triple stores
- Familiarity with property graph solutions
- Mapping business operations into data models, ontologies, schemas
- Working knowledge of triple store ecosystem
- Working knowledge of Enterprise Knowledge Graph architectures
- Awareness of trends in Data Engineering, KG, LLMs
- Solid command of SQL
- Solid command of modern data warehousing/lakehouse concepts
- Solid command of cloud data platforms
- Experience in Data Engineering with hands-on approach
- Fluent in Python
- Ability to convert ideas into productive code
- Advise stakeholders on data into enterprise KG
- Advise stakeholders on applying KG to business use cases
- Knowledge of SAP data and applications preferred
- Strong communication skills
- Strong collaboration skills
- Ability to work effectively in cross-cultural teams
Tasks
- Design and build robust data pipelines
- Ingest, transform, and load structured and unstructured data
- Map source data into ontologies and SHACL schemas
- Develop SPARQL-based transformations
- Operate triple stores in production
- Collaborate with domain specialists and data owners
- Translate requirements into reliable data flows
- Make critical design decisions on data engineering stack
- Integrate with downstream Generative AI applications
- Contribute to thought leadership in Data Engineering
- Present benefits of high-quality Knowledge Graph data
- Propose new business use cases to stakeholders
Work Experience
- 2 years
Education
- Doctoral / PhD
Languages
- English – Fluent
Tools & Technologies
- Data Engineering
- Knowledge Graphs
- RDF
- RDFS
- OWL
- SHACL
- SPARQL
- triple stores
- Neo4j
- SQL
- data warehousing
- lakehouse
- AWS
- GCP
- Azure
- Databricks
- Python
- SAP data
- SAP applications
Benefits
Learning & Development
- Constant learning
- Skill growth
Other Benefits
- Great benefits
- Accessibility accommodations
Mentorship & Coaching
- Team growth support
Informal Culture
- Culture of inclusion
Healthcare & Fitness
- Focus on health and well-being
Flexible Working
- Flexible working models
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(Senior) Data Engineer: RDF Knowledge Graphs and Generative AI(m/w/x)
Building RDF Knowledge Graphs and Generative AI data pipelines for SAP. Mapping source data into ontologies and operating triple stores in production. PhD or Master's degree in CS, AI, physics, or math required.
Requirements
- PhD or Master’s degree in computer science, AI, physics, or mathematics
- 2+ years professional experience in Data Engineering
- Experience with Knowledge Graphs in business context
- Designing and operating large-scale data pipelines
- Deep working proficiency in RDF Knowledge Graph stack
- Hands-on experience operating triple stores
- Familiarity with property graph solutions
- Mapping business operations into data models, ontologies, schemas
- Working knowledge of triple store ecosystem
- Working knowledge of Enterprise Knowledge Graph architectures
- Awareness of trends in Data Engineering, KG, LLMs
- Solid command of SQL
- Solid command of modern data warehousing/lakehouse concepts
- Solid command of cloud data platforms
- Experience in Data Engineering with hands-on approach
- Fluent in Python
- Ability to convert ideas into productive code
- Advise stakeholders on data into enterprise KG
- Advise stakeholders on applying KG to business use cases
- Knowledge of SAP data and applications preferred
- Strong communication skills
- Strong collaboration skills
- Ability to work effectively in cross-cultural teams
Tasks
- Design and build robust data pipelines
- Ingest, transform, and load structured and unstructured data
- Map source data into ontologies and SHACL schemas
- Develop SPARQL-based transformations
- Operate triple stores in production
- Collaborate with domain specialists and data owners
- Translate requirements into reliable data flows
- Make critical design decisions on data engineering stack
- Integrate with downstream Generative AI applications
- Contribute to thought leadership in Data Engineering
- Present benefits of high-quality Knowledge Graph data
- Propose new business use cases to stakeholders
Work Experience
- 2 years
Education
- Doctoral / PhD
Languages
- English – Fluent
Tools & Technologies
- Data Engineering
- Knowledge Graphs
- RDF
- RDFS
- OWL
- SHACL
- SPARQL
- triple stores
- Neo4j
- SQL
- data warehousing
- lakehouse
- AWS
- GCP
- Azure
- Databricks
- Python
- SAP data
- SAP applications
Benefits
Learning & Development
- Constant learning
- Skill growth
Other Benefits
- Great benefits
- Accessibility accommodations
Mentorship & Coaching
- Team growth support
Informal Culture
- Culture of inclusion
Healthcare & Fitness
- Focus on health and well-being
Flexible Working
- Flexible working models
Like this job?
BetaYour Career Agent finds similar jobs for you every day.
About the Company
SAP
Industry
IT
Description
SAP innovations help over four hundred thousand customers worldwide work together more efficiently and use business insight more effectively.
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