Senior Data Architect - Semantics & Know
At Bayer, we are committed to transparency, equal pay for equal work or work of equal value, and objective reward practices in line with EU and local regulations. The minimum monthly gross compensation for this role is 20 240 PLN, with final pay determined based on objective factors such as experience, qualifications, scope of responsibility, and internal alignment. In addition, Bayer offers a competitive and holistic benefits package, including: - Medical care above statutory requirements - Flexible benefits supporting leisure, and well‑being/sports programs - Life, accident, and disability insurance through group coverage - Employer‑supported pension plans with regular company contributions - Home office allowance to support hybrid or remote work - Extra Paid Holidays Benefits may vary depending on country, role, and employment conditions. For Digital Hub Warsaw, we are looking for:
Senior Data Architect – Semantics & Engineering As a Senior Data Architect for Semantics & Knowledge Engineering, you are part of Bayer's Data & AI Team that co-creates domain-specific data products that provide timely, high-quality data to scientists, analysts, and AI agents, with a strong emphasis on semantics as the foundation for AI-readiness. You elicit, structure, and formalize knowledge from domain experts and diverse sources to build ontologies, semantic layers, and knowledge graphs that form the connective tissue of an integrated pharmaceutical data landscape. Your work directly enables secondary data use, self-service analytics, and agentic AI capabilities. This role operates at the intersection of knowledge engineering and data architecture, combining formal knowledge representation with pragmatic, engineering-driven delivery in a cloud-based environment. |
- Bachelor’s Degree in computer science, information science, knowledge engineering, computational linguistics, or a related field, or equivalent practical experience
- Proficiency in designing and implementing data models (conceptual, logical, and physical)
- Advanced knowledge of ontologies and taxonomies with proficiency in Semantic Web technologies, standards, and tools (e.f. RDF, OWL, SHACL, SPARQL, TopBraid EDG)
- Proficiency with graph databases covering both triple stores and labeled-property graph systems, including virtual knowledge graph technologies such as Ontop or Stardog
- Extensive experience API design patterns such as REST and GraphQL
- Strong engineering skills (data engineering, software engineering, or cloud engineering)
- Proficiency in at least one programming language, along with basic Git version control practices
- In-depth knowledge of FAIR Data Principles, Linked Data principles, and Data Mesh architecture concepts, with demonstrated ability to apply them in practice
- Strong analytical and communication skills
- Ability to work collaboratively in a team environment
- High level of accuracy and attention to detail
Preferred
- Experience with semantic layer concepts in modern data platforms such as Databricks, Snowflake, or Microsoft Fabric
- Familiarity with information retrieval systems such as Elasticsearch
- Familiarity with Data Governance solutions (e.g. Collibra)
- Experience designing and implementing Model Context Protocol (MCP) servers
- Hands-on experience with GraphRAG solution design and implementation
- Skills in knowledge retrieval from unstructured data sources
- Understanding of data security principles and practices
- Knowledge of data privacy regulations (e.g., GDPR, CCPA)
- Foundational cloud engineering experience (e.g. AWS, Azure)
- Familiarity with CI/CD practices, for example using GitHub Actions
- Knowledge in the pharmaceutical domain (e.g. LOINC, SNOMED CT, omics, targets, assays, clinical studies, RWE, etc.)