Senior Data Architect - Semantics & Know

Bayer CropScience Limited; Warszawa; Hybrid; PLN 260,000 - 380,000; Full time

Benefits offered by this job

Well-being benefits

Life insurance

Pension plan

Home office allowance

Extra holidays

Job summary

Bayer CropScience Limited is seeking a Senior Data Architect - Semantics & Engineering to structure and formalize domain knowledge into ontologies, taxonomies, and knowledge graphs that power an integrated pharmaceutical data landscape. You will enable self-service analytics and AI-enabled capabilities while applying FAIR and Linked Data principles in a cloud environment.

The role requires deep expertise in semantic web technologies, graph databases, and API design, with a strong emphasis on

Qualifications

• Bachelor's degree or equivalent practical experience in CS/Info science/knowledge engineering.
• Strong knowledge of ontologies, taxonomies, and knowledge graphs.
• Proficiency with Semantic Web standards: RDF/OWL/SPARQL.
• Experience with graph databases and virtual KG tech.
• API design patterns (REST/GraphQL) and cloud engineering basics.
• Familiarity with data governance and privacy concepts (GDPR).

Responsibilities

• Design and implement conceptual, logical, and physical data models and semantic layers.
• Build and maintain ontologies, taxonomies, and knowledge graphs across stores.
• Collaborate with domain experts and engineers to elicit and validate knowledge representations.

Skills

Ontology design

Semantic modelling

Data architecture

REST and GraphQL

Programming fundamentals

Team collaboration

Data governance awareness

Data security basics

Analytical communication

Education

Bachelor's degree in CS/Info Science/Knowledge Engineering

Tools

RDF

OWL

SHACL

SPARQL

TopBraid EDG

Ontop

Stardog

GraphRAG

Databricks

Snowflake

Microsoft Fabric

Elasticseach

Collibra

Git

Job description

• 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.

Senior Data Architect - Semantics & Engineering

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. Embrace FAIR Data Principles and Linked Data standards to promote a data culture that shifts from siloed thinking to networked, democratized data use.

Required: 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 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.)

Data Modelling

Design and implement conceptual, logical, and physical data models and semantic layers to enable consistent use. Design, build and maintain ontologies, taxonomies, and knowledge graphs using both triple stores and labeled-property graph technologies, including virtual knowledge graph approaches where appropriate. Collaborate with domain experts, data scientists, data engineers, and product teams to elicit tacit knowledge, validate knowledge representations, and ensure accuracy and completeness. Deliver well-designed solutions to integrate, unify and synchronize data across systems. Design data-oriented APIs and integration patterns that decouple data from source systems and make knowledge structures interoperable and consumable by humans, systems, and AI agents. Design and implement appropriate measure to protect data fromunauthorized access, corruption, or theft, ultimately ensuring confidentiality, integrity, and availability of data to maintain trust in data and prevent legal, operational, regulatory and financial risks.