Senior Knowledge Engineer at SAP

Department: Enabling FunctionsSeniority in posting: Professional

Language

Compensation

PLN 20,240/mo

Setup: Hybrid
Location: Masovian Voivodeship
Type: Full-time
Level: senior
Added to Metaintro: Sep 4, 2026

Summary from listing

Bayer is hiring a Senior Knowledge Engineer for its Data & AI team in Warsaw. The role focuses on building scalable, AI-ready data foundations through data architecture, knowledge modelling, knowledge graphs, semantic technologies, data integration, APIs, and governance. The engineer will collaborate with domain experts, data engineers, data scientists, and product teams to support analytics, AI, and scientific innovation, with a minimum monthly gross compensation of 20,240 PLN and a hybrid work model.

Required Skills

Data modelling
Data architecture
Knowledge graphs
Graph databases
Semantic technologies
Data integration
APIs
Metadata management
Cloud engineering
Git
Stakeholder management

Additional Information

Minimum Education: Bachelor's degree in Computer Science, Information Systems, Data Engineering, Knowledge Engineering, Computational Linguistics, or a related field, or equivalent practical experience.
Required Previous Experiences: Strong experience in data modelling, including conceptual, logical, and physical models.
Experience in data architecture, knowledge engineering, data engineering, metadata management, or closely related disciplines.
Experience with knowledge graphs, graph databases, semantic technologies, or metadata-driven architectures.
Hands-on experience designing APIs and data integration solutions.
Strong engineering background in data engineering, software engineering, cloud engineering, or platform engineering.
Preferred Qualifications: Experience with graph database technologies such as Neo4j, Stardog, GraphDB, Amazon Neptune, or TigerGraph.
Experience with ontology modelling, taxonomies, semantic modelling, or Semantic Web standards.
Experience with modern cloud data platforms such as Databricks, Snowflake, Microsoft Fabric, AWS, Azure, or GCP.
Familiarity with metadata management and data governance solutions.
Experience designing AI-ready architectures, knowledge retrieval solutions, GraphRAG, RAG, or Agentic AI applications.
Understanding of FAIR Data Principles, Linked Data, Data Mesh, or comparable modern data architecture approaches.
Familiarity with Elasticsearch or enterprise search technologies.
Experience with CI/CD practices and DevOps tooling.
Knowledge of data privacy, security, and regulatory requirements.
Experience within life sciences, healthcare, pharmaceutical, or research environments.