20 meilleures offres (data engineer – data & ai, zürich, zh) (à pourvoir)

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- 100%
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Data & Backend Engineer — Healthcare AI

Enzian Labs AG
Zürich, ZH

Postuler rapidement

Détails de l'emploi

100%
Il y a 19 heures

Qualifications

Relational databases
Anglais
Google Cloud Platform
Bases de données
Niveau Licence
Allemand

Description complète du poste

Position: Data & Backend Engineer - Healthcare AI
Job Type: Full-Time
Start Date: By agreement
Location: Zürich - hybrid, with most working days in the office
Language: English; German is a plus

About the Role

At Enzian Labs, we believe technology can make healthcare work better for everyone - from patients and clinicians to the people operating complex healthcare systems. We build software and AI solutions that turn fragmented information and difficult workflows into useful, reliable products.

We are looking for a Data & Backend Engineer to help us scale and further develop our existing healthcare solutions, expanding them to new projects and use cases.

You will develop backend services, data pipelines, integrations, and AI-enabled workflows that transform complex healthcare data into dependable, usable systems. You will work closely with our technical lead and product stakeholders, owning substantial parts of implementation from initial design through production deployment.

This is a hands-on individual-contributor role for an experienced engineer who enjoys data-intensive systems, pragmatic architecture, and solving meaningful problems in healthcare, while embracing the entrepreneurial spirit of a growing start-up.

Key Responsibilities

Backend Engineering: Design and build reliable backend services, APIs, integrations, and asynchronous processing workflows.

Data Pipelines: Develop systems that ingest, transform, validate, and export structured and unstructured data from multiple sources.

Data Modelling: Translate complex domain requirements into clear, maintainable data models that support both operational workflows and downstream analysis.

Applied AI: Integrate LLMs and other AI capabilities into production workflows, with appropriate evaluation, validation, and failure handling.

Production Delivery: Own functionality from technical design through implementation, testing, deployment, monitoring, and continued improvement.

Product Collaboration: Work closely with technical leadership and product stakeholders to clarify requirements, identify trade-offs, and focus development on the underlying user and business problem.

Security and Data Protection: Build with appropriate care for sensitive healthcare data, including privacy, access control, auditability, and secure infrastructure.

Reusable Foundations: Turn lessons and technical components from successful pilots into maintainable capabilities that can support future HealthX projects.

Minimum Qualifications

Experience: At least 3 years of professional software-engineering experience, with evidence of independently delivering meaningful backend or data-intensive functionality.

Data Engineering: Experience processing, transforming, and validating data, including diagnosing data-quality and integration problems.

Backend Systems: Practical experience designing APIs, working with relational databases, and building services that run reliably in production.

Engineering Fundamentals: A sound understanding of testing, version control, observability, security, and maintainable software design. Clean code, maintainability and architecture.

End-to-End Ownership: Comfortable moving between requirements, implementation, deployment, and production troubleshooting. Able to work through ambiguity, ask useful questions, and make pragmatic technical decisions based on real user needs.

Preferred Qualifications

Healthcare Experience: Experience in healthcare, health technology, clinical data, or another privacy-sensitive or regulated environment. Familiarity with EU MDR and Swiss medical device regulation (MepV/MedDO) is a plus.

Applied AI: Experience building applications with LLMs, document processing, information extraction, evaluation pipelines, or related AI technologies.

Cloud Platforms: Practical experience with GCP or another major cloud platform, including managed databases, containerized workloads, and cloud storage.

Data Standards: Familiarity with healthcare data standards or models such as OMOP is helpful but not required.

Education: A university degree in computer science, data science, engineering, or a related discipline is preferred; strong equivalent professional experience is equally welcome.

Language Skills: German is a plus, particularly for collaboration with Swiss clients and stakeholders.

Engagement Details

This is a permanent, full-time position based in Zürich. We work in a hybrid setup, with most working days spent together in the office.

You will join a small team where engineers remain close to product decisions and the real-world impact of their work. You will have meaningful ownership without being expected to manage a team or act as the technical lead.

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Je souhaite recevoir la dernière alerte Emploi pour les postes de ce type : data engineer – data & ai (zürich, zh)

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