About the role
- Work mode - fully remote.
- Assignment type: B2B
- Start - 01.09.2026.
- Contract length > 10-12 months + extensions.
- Language - English.
- Industry - pharmaceutical.
- Recruitment process - 2 interviews with the client.
- Workload: Full time.
This role is for a Senior Software Engineer – Knowledge Graph , responsible for maintaining data quality, integration, and development of the knowledge graph platform, a vital asset that consolidates diverse drug discovery and gene biology data.
Responsibilities:
- Own data quality: Define and enforce data validation, provenance tracking, and quality metrics across all data sources in the graph.
- Integrate data sources: Collaborate with internal and external data providers to ingest, normalize, and harmonize heterogeneous biomedical datasets.
- Maintain the knowledge graph: Manage the Neo4j schema, data modeling, and pipeline reliability.
- Prepare data for AI/analytics: Ensure graph data supports AI and analytics use cases, including the Blindspot Analysis.
- Collaborate cross-functionally: Work with research scientists, data scientists, and engineers to align scientific needs with reliable data solutions.
Must Haves:
- Strong Python skills for data engineering and pipeline development.
- Hands-on experience with Neo4j (Cypher, schema design, query optimization).
- Proven experience integrating multiple heterogeneous biomedical data sources.
- Deep understanding of data quality practices in production environments.
- Experience resolving schema, identifier, and consistency issues directly with data providers.
- Familiarity with biomedical standards and identifiers (UniProt, Ensembl, ChEMBL, etc.).
- Strong communication skills with cross-functional scientific and technical teams.
Nice to Haves:
- Experience in pharma, biotech, or academic drug discovery.
- Advanced degree (MSc/PhD) in a relevant field.
- Familiarity with graph ML, embeddings, or search/retrieval concepts.
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