At a Glance
- Tasks: Build and maintain data infrastructure for innovative wearable health technology.
- Company: Early-stage health tech company with a close-knit team.
- Benefits: High level of ownership, collaborative environment, and impactful work.
- Other info: Opportunity to influence data governance and research workflows.
- Why this job: Shape the future of wearable health data and make a real difference.
- Qualifications: Experience with time-series data, Python, and clinical datasets.
The predicted salary is between 45000 - 55000 £ per year.
An early-stage health technology company is seeking a Clinical Data Engineer to help build and maintain the data infrastructure underpinning a novel class of wearable health biomarkers.
This is a highly impactful role within a close-knit team, where you'll work at the intersection of clinical research and data engineering — collaborating with clinicians, researchers, and ML teams to ensure that raw physiological signals are transformed into trustworthy, analysis-ready datasets.
You'll play a key role in shaping how wearable health data is validated, governed, and deployed at scale.
In this position, you'll be responsible for designing and implementing multimodal data pipelines, cleaning and synchronising real-world clinical datasets, and building tooling for annotation, quality control, and versioning.
You'll also support clinical study design and ensure all data processes meet regulatory and privacy requirements.
What they're looking for: Strong experience with time-series data engineering and analysis Proficiency in Python and relevant data frameworks Experience working with clinical or biomedical datasets Solid understanding of data quality, bias, and reproducibility in health research Ability to collaborate effectively across clinical and engineering stakeholders Familiarity with data governance, privacy standards, and audit requirements Why consider it: Opportunity to build the clinical evidence foundation for a genuinely novel area of wearable health technology High level of ownership and influence over data infrastructure and research workflows Collaborative environment spanning clinical, research, and ML disciplines Work that directly shapes how wearable health data is trusted and interpreted at scale If this role is interesting to you then apply now or reach out to Charles Duran at IC Resources.
Data Engineer in Cambridge employer: Intellectual Capital Resources
Join a dynamic and innovative audio AI product company that prioritises employee growth and collaboration in a fully remote environment. With a strong focus on cutting-edge technology and a culture of mentorship, you'll have the opportunity to work alongside talented professionals while contributing to impactful projects that enhance sound experiences globally. Enjoy the flexibility of remote work, competitive benefits, and a commitment to fostering a supportive and inclusive workplace.
Contact Details:
Intellectual Capital Resources Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer in Cambridge
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Intellectual Capital Resources!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Data Engineer at Intellectual Capital Resources.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Intellectual Capital Resources.
✨Apply Directly through Our Website
When you find a suitable opening like Data Engineer at Intellectual Capital Resources, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Data Engineer in Cambridge
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Intellectual Capital Resources, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Intellectual Capital Resources. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Intellectual Capital Resources
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Intellectual Capital Resources!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
