Unique opportunity to contribute to the development of Knowledge Graph solutions covering SAP domain knowledge and providing grounding to LLM applications (e.g. Joule).
Build ETL pipelines to lead the ingestion of data, metadata, and other development artifacts into our Knowledge Graph.
Partner with domain experts across different lines of business (LoB) at SAP, understand and interpret their data, metadata, and other development artifacts and make it consumable in our Knowledge Graph.
Extract relevant information from various LoB data sources for further processing and enrichment of our large-scale Knowledge Graph serving the Foundation Model and other LLM use cases.
Contribute to design and build stable and scalable applications.
Guide and inspire the Business Knowledge Graph team with your expertise in understanding the data.
Guide junior project members and shape collaborations with stakeholders.
Make critical design decisions regarding the selection and implementation of underlying technologies.
Contribute to thought leadership in an entirely new approach towards generative AI, using the combination of Knowledge Graphs and Foundation Models in business contexts.
What you bring
5+ years of related professional experience in Software Engineering with at least 2 years of professional experience as a data engineer.
Bachelor's or master’s degree in computer science, Artificial Intelligence, physics, mathematics, or other relevant disciplines.
Proficiency in Python as well as experience building ETL pipelines with Metaflow, Airflow or similar frameworks.
Hands-on experience in any of the cloud stacks (AWS, GCP, Azure, BTP).
Experience in building data pipeline activities for projects, ideally related to data science projects, e.g. with Large Language Models.
Experience with object stores, relational databases or vector databases.
Understanding of SAP S/4HANA backend (ABAP and Data Dictionary) and data models (e.g., VDM, CDS Views, RAP, OData) is a plus.
Experience with Knowledge Graph technologies (e.g., RDF, SPARQL) is a plus.
Curiosity and interest to experiment and adopt new technologies and frameworks.
Strong communication, collaboration and leadership skills, experience with agile methodology and an ability to work effectively in distributed, cross-cultural teams.