At a Glance
- Tasks: Transform biomedical datasets into AI-ready assets and build robust data engineering pipelines.
- Company: Join a pioneering AI Accelerator in London focused on biomedical innovation.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Other info: Collaborative environment with cutting-edge technology and excellent career advancement opportunities.
- Why this job: Make a real impact in healthcare by advancing AI capabilities in biomedical research.
- Qualifications: PhD in a relevant field and strong experience in data engineering for machine learning.
The predicted salary is between 60000 - 80000 € per year.
The AI Accelerator is a brand-new, London-based hub, sitting within Computational Innovation (CI), which is a global organisation comprising computational biology, human genetics, data excellence and AI expertise. The purpose of CI’s AI Accelerator is to provision production-quality, versatile, foundational biomedical AI capabilities that can be adapted and deployed to improve and accelerate portfolio decision-making and increase the probability of success, by furthering understanding of the biology driving patient outcomes and identifying mechanisms involved in disease.
A core component of the AI Accelerator is AI Enablement, a team focused on ensuring that the accelerator’s model provisioning teams can design, build and deploy versatile biomedical foundation models that can enhance human understanding of disease biology and help identify potential targets, biomarkers and patient segments for further research. This will be achieved by provisioning AI-ready, integrated, multimodal data for distributed training, managing the model lifecycle and partnering with the IT organisation to ensure that model builders and downstream users have the necessary infrastructure and tooling to prototype, implement, adapt and deploy AI capabilities to advance the portfolio.
Key Responsibilities
- Transform harmonised datasets into AI-ready assets suitable for large model pre-training and fine-tuning within the defined standards and specifications.
- Build and maintain entity linking pipelines that connect patients and biomedical entities across modalities.
- Build and maintain cross-modal integration pipelines to support multimodal training, fine-tuning and inference.
- Ensure pipelines and datasets are built and operated in accordance with data access permissions, consent conditions and usage restrictions.
- Maintain data lineage and provenance throughout.
- Build and maintain biomedical benchmark datasets with versioning and documentation.
- Write clean, well-tested, well-documented code that meets the required engineering standards.
- Contribute to code reviews within the data engineering team.
- Stay current with advances in data engineering tooling and practices relevant to biomedical AI.
Required Qualifications
- PhD in Machine Learning, Computer Science, Bioinformatics, Computational Biology or a related quantitative field.
- Strong hands‑on experience in data engineering for machine learning.
- Experience working with at least one biomedical data modality in a data engineering context.
- Practical experience with entity linking or record linkage, ideally in a biomedical or clinical context.
- Strong understanding of biomedical data characteristics such as variant data formats, expression matrices, clinical coding standards such as SNOMED and ICD-10.
- Proficiency with modern data engineering tools.
- Familiarity with data governance frameworks applicable to biomedical and clinical data.
- Familiarity with Trusted Research Environments or controlled access biomedical data environments.
- Experience with biomedical ontology systems and identifier mapping across modalities.
- Contributions to open-source data engineering or bioinformatics tooling.
Senior Data Engineer employer: Boehringer Ingelheim GmbH
As a Senior Data Engineer at the AI Accelerator in London, you will be part of a pioneering team dedicated to advancing biomedical AI capabilities. The company fosters a collaborative and innovative work culture, offering ample opportunities for professional growth and development in a cutting-edge field. With a focus on employee well-being and a commitment to impactful research, this role provides a unique chance to contribute to meaningful projects that enhance patient outcomes.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data engineering projects, especially those related to biomedical AI. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice common data engineering scenarios and be ready to discuss how you've tackled challenges in past projects.
✨Tip Number 4
Don't forget to apply through our website! We love seeing applications directly from candidates who are excited about joining the AI Enablement team. It shows initiative and enthusiasm, which we really appreciate!
We think you need these skills to ace Senior Data Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Senior Data Engineer role. Highlight your experience with data engineering, especially in biomedical contexts, and showcase any relevant projects or tools you've worked with. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about AI in healthcare and how your background makes you a perfect fit for our AI Enablement team. Keep it engaging and personal – we love to see your personality come through!
Showcase Your Technical Skills:In your application, don't forget to highlight your technical skills, especially those related to data engineering tools and practices. Mention any experience with entity linking, cross-modal integration, or working with biomedical datasets. We’re keen on seeing your hands-on experience!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, you’ll find all the details about the role and our team there. We can’t wait to hear from you!
How to prepare for a job interview at Boehringer Ingelheim GmbH
✨Know Your Data Inside Out
Make sure you’re well-versed in the specifics of biomedical data, including variant data formats and clinical coding standards like SNOMED and ICD-10. Brush up on your understanding of multi-omics and how to transform harmonised datasets into AI-ready assets, as this will likely come up during your interview.
✨Showcase Your Technical Skills
Be prepared to discuss your hands-on experience with modern data engineering tools. Bring examples of your previous work, especially any projects involving entity linking or cross-modal integration pipelines. This will demonstrate your practical knowledge and ability to contribute to the team right away.
✨Understand the Bigger Picture
Familiarise yourself with the goals of the AI Accelerator and how your role as a Senior Data Engineer fits into the broader mission of improving patient outcomes. Showing that you understand the impact of your work on decision-making and research can set you apart from other candidates.
✨Prepare for Code Reviews
Since code quality is crucial, be ready to discuss your approach to writing clean, well-documented code. You might even be asked to participate in a mock code review, so think about how you would provide constructive feedback and ensure adherence to engineering standards.
