About the job
About us
Owkin is an innovative AI-driven company dedicated to unraveling the complexities of biology. We are developing the first Biology Super Intelligence (BASI) by seamlessly integrating advanced biological large language models, multimodal patient data, and intelligent software. Central to our vision is Owkin K, an AI copilot, powered by our proprietary LLM, Owkin Zero, designed to assist researchers, clinicians, and drug developers in advancing their understanding of biological processes, validating scientific hypotheses, and accelerating the delivery of precise diagnostics and therapies.
Position is based in our London office or remotely in the UK and Germany.
Please submit your CV in English.
About the role:
As a member of our Engineering team, you will play a crucial role in designing, constructing, and optimizing scalable ETL/ELT pipelines with Airflow, aimed at efficiently processing intricate datasets while ensuring high reliability and performance. Your responsibilities will include organizing and structuring data systems in alignment with business objectives and showcasing your expertise in scientific and healthcare information systems to develop data products that support machine learning and AI research. Attention to detail and the ability to manage high-volume, complex workstreams while prioritizing multiple deadlines will be essential. Strong interpersonal skills are required to collaborate effectively with various stakeholders in the biotechnology sector, and you will be instrumental in streamlining production workflows for scientific processing and quality assurance.
- Organize and structure data systems at both macro and micro levels, designing and implementing data architectures that support business goals.
- Optimize data pipelines for performance, reliability, and scalability.
- Design, build, and maintain scalable ETL/ELT pipelines with Airflow to process large-scale, complex datasets.
- Demonstrate the ability to deliver data products that are valuable for machine learning and AI research and development (data models, metadata, and semantics).
- Exhibit strong organizational skills to effectively manage high-volume, complex workstreams while prioritizing multiple deadlines.
- Showcase knowledge of scientific and healthcare information systems and relevant software tools.
