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 clinical research workflows and data governance.
- Why this job: Shape the future of wearable health data and make a real difference.
- Qualifications: Experience in time-series data engineering and proficiency in Python.
The predicted salary is between 50000 - 70000 £ 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
- Building tooling for annotation, quality control, and versioning
- Supporting clinical study design
- Ensuring 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
Clinical Wearable Data Engineer | Time-Series & Governance employer: IC Resources
Join an innovative early-stage health technology company where your role as a Clinical Data Engineer will be pivotal in shaping the future of wearable health biomarkers. With a strong emphasis on collaboration, you'll work closely with clinicians and researchers in a supportive environment that values your contributions and offers significant opportunities for professional growth. Enjoy the unique advantage of being part of a close-knit team dedicated to making a meaningful impact in healthcare through cutting-edge data engineering.
StudySmarter Expert Advice🤫
We think this is how you could land Clinical Wearable Data Engineer | Time-Series & Governance
✨Tip Number 1
Network like a pro! Reach out to professionals in the health tech space, especially those working with wearable data. Use platforms like LinkedIn to connect and engage with them; you never know who might have a lead on your dream job!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your experience with time-series data engineering and analysis. Include projects that demonstrate your proficiency in Python and how you've tackled real-world clinical datasets.
✨Tip Number 3
Prepare for interviews by brushing up on data governance and privacy standards. Be ready to discuss how you would ensure compliance in your work. This will show potential employers that you’re not just technically skilled but also aware of the regulatory landscape.
✨Tip Number 4
Don’t forget to apply through our website! We love seeing candidates who are genuinely interested in joining our team. Tailor your application to highlight your collaborative spirit and how you can contribute to shaping the future of wearable health data.
We think you need these skills to ace Clinical Wearable Data Engineer | Time-Series & Governance
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with time-series data engineering and Python. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or achievements!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re passionate about wearable health technology and how your background in clinical datasets makes you a perfect fit for our team. Let us know what excites you about this role!
Showcase Collaboration Skills:Since we work closely with clinicians and researchers, it’s important to highlight any past experiences where you’ve successfully collaborated across different teams. Share examples that demonstrate your ability to communicate effectively and work towards common goals.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates. Plus, it shows us you’re keen to join our team!
How to prepare for a job interview at IC Resources
✨Know Your Data Inside Out
Make sure you brush up on your knowledge of time-series data engineering and analysis. Be prepared to discuss specific projects where you've worked with clinical or biomedical datasets, and how you ensured data quality and reproducibility. This will show that you understand the nuances of the role.
✨Showcase Your Technical Skills
Since proficiency in Python and relevant data frameworks is key, be ready to demonstrate your coding skills. You might be asked to solve a problem on the spot, so practice common data manipulation tasks beforehand. Having examples of your work can also help illustrate your capabilities.
✨Understand the Regulatory Landscape
Familiarise yourself with data governance, privacy standards, and audit requirements relevant to health research. Being able to discuss how you’ve navigated these in past roles will highlight your readiness for this position and your commitment to ethical data handling.
✨Emphasise Collaboration
This role involves working closely with clinicians, researchers, and ML teams, so be prepared to talk about your experience collaborating across disciplines. Share examples of how you’ve effectively communicated complex data concepts to non-technical stakeholders, as this will demonstrate your ability to bridge the gap between clinical and engineering teams.
