Liom is a Swiss health-tech startup dedicated to revolutionizing the field of personalized health monitoring. Our objective is to develop the first health wearable monitoring glucose non-invasively. We will launch our wearable as a consumer product in the United States and Europe in 2028. Our team consists of over 35 staff, with deep expertise in product development, and the required engineering as well as scientific disciplines. We are operating out of our lab facilities in Pfäffikon SZ, Switzerland.
Liom is preparing to 100× its data acquisition capacity. Our visual health‑data—combined with rich metadata—is the foundation for real‑world clinical insights and downstream data‑science models. To support this next phase of growth, we are building a new data platform on Google Cloud that can scale with our ambitions.
As a Data Engineer, you will take ownership of how Liom ingests, structures, validates, and operationalises data across the company. You’ll work across backend services, data engineering, and platform architecture, helping us build systems that are secure, reliable, and ready for clinical‑grade scale.
This is a hands‑on role in a fast‑moving startup environment, ideal for someone who wants to shape the technical direction of a company making real‑world health impact.
Responsibilities
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Steer the design and implementation of Liom’s next‑generation data platform on Google Cloud.
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Define and own approaches for:
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Data lineage and traceability
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Model evaluation, pipeline management & calibration workflows
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Quality controls and automated validation
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Data readers for object‑based datasets
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Balancing relational vs. object‑based data models
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Work closely with data science, product, and lab teams to ensure data is accessible, high‑quality, and fit for downstream use.
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Translate business needs into technical architecture, and clearly communicate trade‑offs to both technical and non‑technical audiences.
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Support emerging needs for unstructured data from business, sales, and operations teams.
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5+ years experience generating business value through data engineering
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Comfortable in a Python‑first engineering environment.
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Bring a DevOps mindset, balancing security, reliability, and operational pragmatism.
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Thrive in a startup culture—comfortable stepping outside your comfort zone and learning rapidly.
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Be a team player who values collaboration, clarity, and shared ownership.
Nice to Have
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Hands‑on experience with Cloud Run, Cloud Functions, or serverless patterns.
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Familiarity with GitHub Actions and modern CI/CD pipelines.
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Experience with data governance, schema evolution, or ML‑ops workflows.
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Exposure to health‑tech, regulated data, or scientific computing environments.
Diversity
With 15 nationalities in the company, we strive to build a diverse and exciting environment. We care about diversity and equal opportunities and encourange everyone to apply.
Mentorship & Career Growth
Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship.
Join an amazing, collaborative team!
You’ll be supported by knowledgeable, approachable colleagues and have plenty of chances to learn, exchange ideas, and hear new perspectives.
The interview process consists of three stages:
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Introduction video call
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Technical Interview
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On-site interview
