Data Engineer

Lead the development and scaling of our scientific knowledge graph—ingesting, structuring, and enriching massive datasets from research literature and global data sources into meaningful, AI-ready insights. 

Requirements: 

- Strong experience with knowledge graph design and implementation (Neo4j, RDFLib, GraphQL, etc.). 

- Advanced Python for data engineering, ETL, and entity processing (Spark/Dask/Polars). 

- Proven track record with large dataset ingestion (tens of millions of records). 

- Familiarity with life-science or biomedical data (ontologies, research metadata, entity linking). 

- Experience with Airflow/Dagster/dbt, and data APIs (OpenAlex, ORCID, PubMed). 

- Strong sense of ownership, precision, and delivery mindset. Nice to Have: 

- Domain knowledge in life sciences, biomedical research, or related data models. 

- Experience integrating vector/semantic embeddings (Pinecone, FAISS, Weaviate).

We offer:

• Attractive financial package

• Challenging projects

• Professional & career growth

• Great atmosphere in a friendly small team