Hybrid AI Data Engineer in Austria - Flexible Hours

GE HealthCare; Zipf; Hybrid; EUR 68,000 - 83,000; Full time

Benefits offered by this job

Flextime and flexible working hours

Free electric charging stations and on

Ample parking facilities on company

Birthday day off

Company shuttle to Zipf train station

Job summary

GE HealthCare is hiring an AI Data Engineer in Zipf, Austria to develop reusable data tooling, manage shared data infrastructure, and evaluate ultrasound-focused platforms worldwide.

In this hybrid role, you will turn requirements into tested solutions, design experiments, and collaborate across teams to standardize interfaces and improve data workflows while ensuring privacy, security, and compliance for healthcare data.

Qualifications

• Master’s degree in computer science, data engineering, software engineering, information systems, AI, or a related field.
• Hands-on experience developing and operating data pipelines, shared software tools, or AI development infrastructure.
• Practical knowledge of cloud environments, containers, Linux, and data workflow orchestration.
• Strong programming skills in Python and SQL, with experience designing APIs, integrating services, and working with structured and unstructured data.
• Experience with Git, automated testing, code review, continuous integration and delivery, and maintainable software packaging.
• Ability to design controlled technical experiments, benchmark platforms, and communicate results and trade-offs clearly.
• Understanding of AI data workflows, including curation, annotation, dataset versioning, and training and validation data preparation.
• Awareness of security, privacy, and traceability requirements when handling healthcare data.
• Fluent English and the ability to collaborate with globally distributed engineering, data science, and infrastructure teams.

Responsibilities

• Translate cross-team requirements into working solutions and operational procedures.
• Design and run reproducible experiments, proofs of concept, and benchmarks on third-party and internal data management and AI development platforms using representative ultrasound team workflows.
• Assess functional fit, interoperability, performance, scalability, usability, interoperation cost against agreed requirements. Document methods, results, limitations, and recommendations to inform platform selection.
• Collaborate with individual teams to extend internally developed tools for use across the ultrasound organization. Refactor team-specific assumptions into configurable modules and standardize interfaces to increase reuse.
• Develop and maintain shared libraries, services, and connectors, with automated tests, versioned packages, and deployment workflows that make adoption and maintenance easier for other teams.
• Build and operate data ingestion, transformation, and validation pipelines supporting data curation, annotation, dataset preparation, and AI development.
• Carry out day‑to‑day operation of agreed shared tools and environments, including configuration, updates, job monitoring, troubleshooting, and performance tuning, in coordination with platform owners.
• Support teams with platform onboarding, tool integration, and data or workflow migrations, and provide practical feedback on gaps in shared infrastructure.
• Implement data quality checks, logging, and traceability, and automate approved data access, de‑identification, and retention workflows with guidance from the responsible specialists.
• Investigate pipeline and platform failures, reproduce issues, and work with internal platform teams or external vendors to resolve root causes and prevent recurrence.
• Create user guides, integration examples, and operational runbooks; provide training and technical support so teams can adopt, operate, and contribute to shared tools.

Skills

Fluent English

Collaborative

Testing & documentation

Experiment design

Education

Master’s degree in computer science, data engineering, software engineering, information systems, AI, or related field

PhD in computer science, data engineering, software engineering, information systems, AI, or related field

Tools

Git

CI/CD

APIs

Docker/Kubernetes

Cloud platforms

Job description

GE HealthCare is hiring an AI Data Engineer in Zipf, Austria to develop reusable data tooling, manage shared data infrastructure, and evaluate ultrasound-focused platforms worldwide.

In this hybrid role, you will turn requirements into tested solutions, design experiments, and collaborate across teams to standardize interfaces and improve data workflows while ensuring privacy, security, and compliance for healthcare data.