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- Tasks: Design and optimise data pipelines using Airflow for complex datasets.
- Company: Owkin, an innovative AI company revolutionising biology with cutting-edge technology.
- Benefits: Friendly work environment, international team, and opportunities for growth.
- Why this job: Join a mission-driven team to impact healthcare and biology through data engineering.
- Qualifications: Master's degree in computer science and 5+ years as a Data Engineer.
- Other info: Remote work options available in the UK and Germany.
The predicted salary is between 36000 - 60000 £ per year.
Owkin is an AI company on a mission to solve the complexity of biology. It is building the first Biology Super Intelligence (BASI) by combining powerful biological large language models, multimodal patient data, and agentic software. At the heart of this system is Owkin K, an AI copilot and its new LLM fine‑tuned on biology called Owkin Zero, used by researchers, clinicians, and drug developers to better understand biology, validate scientific hypotheses, and deliver better diagnostics and therapies faster. Position is based in our London office or remotely in UK and Germany.
About The Role
You will be part of the Engineering team. This role involves designing, building, and optimizing scalable ETL/ELT pipelines with Airflow to process complex datasets efficiently while ensuring reliability and performance. You will organize and structure data systems, aligning them with business objectives, and demonstrate expertise in scientific and healthcare information systems to deliver data products tailored for machine learning and AI research. Clear reporting and meticulous attention to detail are essential, as is the ability to manage high‑volume, complex workstreams while prioritizing multiple deadlines. The role requires professional interpersonal skills to collaborate with diverse stakeholders in biotechnology and the ability to streamline 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 ability to deliver data products useful for machine learning and AI research and development (data models, metadata and semantics).
- Strong organizational skills to effectively manage high‑volume, complex workstreams while prioritizing multiple deadlines.
- Demonstrate knowledge of scientific and healthcare information systems and data sources and relevant software tools.
- Demonstrate ability to handle a variety of activities across operational delivery and development initiatives.
- Demonstrate professional interpersonal skills with ability to work both independently and collaboratively with a variety of stakeholders on complex biotechnology areas.
- Streamline the process of taking scientific processing and quality check in production, ensuring proper monitoring of the production workflows.
In Particular, You Will
- Design and optimize data pipelines using Airflow.
- Develop robust solutions in Python and SQL.
- Design, develop, and operate scalable ETL/ELT pipelines to process and transform datasets.
- Work with cross‑functional teams, including data scientists, business developers, software engineers and biomedical researchers to deliver high‑quality data solutions.
- Manage and monitor containerised data infrastructures with Docker and Kubernetes and other cloud platforms.
- Implement and enforce best practices for data governance, security, and compliance.
- Build, optimise and maintain data architectures, including data lakes, data warehouses, and analytical insights.
- Productionise the data processing pipelines, setting and enforcing standards and best practices across scientific teams to deliver high quality data in an efficient and scalable way.
About You
Required qualifications / experience:
- Master degree in computer sciences or specialise in Data.
- Significant experience (5+ years) as a Data Engineer and have good knowledge of DataOps practices.
- Experience in Python and SQL and familiarity with R.
- Experience in architectural design of complex data platforms.
- Proficient in the technologies like Airflow, AWS Step Functions, PostgreSQL, Docker, Kubernetes, Grafana, Infrastructure as Code.
- Autonomous, meticulous, and enjoy teamwork.
- Software development with a focus on code quality, simplicity, maintainability.
- Experience in designing data architecture and building data products.
- Experience handling sensitive personal information.
Preferred Qualifications/bonus:
- Knowledge in healthcare or biology areas.
- Debugging and refactoring skills.
What we offer
- Friendly and informal working environment.
- Opportunity to work with an international team with high technical and scientific backgrounds.
Equal Opportunity Employer
Owkin is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, sex, gender, sexual orientation, age, color, religion, national origin, protected veteran status or on the basis of disability.
Data Engineer employer: Owkin
Contact Detail:
Owkin Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. A friendly chat can sometimes lead to job opportunities that aren't even advertised.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data engineering projects. Whether it's a GitHub repo or a personal website, let your work speak for itself.
✨Tip Number 3
Prepare for interviews by brushing up on common data engineering questions and scenarios. Practice explaining your thought process clearly; it’s all about demonstrating your problem-solving skills.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive!
We think you need these skills to ace Data Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with data engineering, especially with tools like Airflow and Python. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects!
Show Your Passion for Biology: Since we’re all about solving biological complexities, it’s a great idea to include any relevant experience or interest in biology or healthcare. This will help us see how you fit into our mission at Owkin.
Be Clear and Concise: When writing your application, keep it straightforward and to the point. We appreciate clarity, so make sure your achievements and skills are easy to spot. Remember, less is often more!
Apply Through Our Website: We encourage you to submit your application through our website. It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at Owkin
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, like Airflow, Python, and SQL. Brush up on your knowledge of Docker and Kubernetes too, as they’ll likely come up during technical discussions.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific examples where you've designed and optimised data pipelines or tackled complex datasets. Use the STAR method (Situation, Task, Action, Result) to structure your answers and highlight your impact.
✨Understand the Business Context
Familiarise yourself with how data engineering supports business objectives, especially in the biotech field. Be ready to explain how your work can help streamline processes and improve outcomes in healthcare and research.
✨Demonstrate Team Collaboration
Since the role involves working with cross-functional teams, be prepared to share experiences where you’ve successfully collaborated with data scientists, software engineers, or other stakeholders. Highlight your interpersonal skills and ability to work both independently and as part of a team.