AI Data Architect (f/m/d) at GE HEALTHCARE
At a glance
- Company
- GE HEALTHCARE
- Location
- Austria
- Work arrangement
- On-site
- Experience
- 5–10 years
- Working hours
- 40 hours
- Visa sponsorship
- Offered, according to the listing
- Posted
- Added to The Stack
✨ The Stack take on this GE HEALTHCARE job
- 🏢 This is GE HEALTHCARE's only job here right now
Updated 2026-11-05, from our data and official sources.
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About the role
Responsibilities:
- Define and evolve the global AI data architecture for ultrasound AI development: reference architectures, standards and patterns.
- Align distributed product and engineering teams on shared platforms, tools, pipelines, metadata and governance.
- Lead build-vs-buy evaluations, vendor assessments, proofs of concept and commercial due diligence.
- Own the AI data architecture roadmap, prioritisation, investment proposals and capacity planning.
- Partner with cloud, infrastructure and security teams to standardise pipelines, observability, lineage and data quality practices.
- Enable compliant healthcare data handling: de-identification, access controls, retention, sharing and lifecycle management.
- Coordinate onboarding, migration and retirement of platforms; lead architecture and incident reviews and document decisions.
Requirements:
- Master’s degree in computer science, data engineering, AI or related field and progressive experience in data architecture or AI platforms.
- Strong knowledge of modern cloud data platforms, metadata/lineage tooling, registries and scalable data pipelines.
- Experience with healthcare data requirements, privacy/de-identification and regulatory compliance.
- Proven ability to evaluate vendors, lead technical-commercial negotiations and run POCs.
- Demonstrated stakeholder leadership: influence cross-functional global teams and translate technical strategy to business outcomes.
- Solid understanding of security, interoperability and platform engineering best practices.
Responsibilities
You will shape the global data architecture for AI development across ultrasound teams by aligning distributed teams on shared platforms and infrastructure. Additionally, you will define reference architectures, lead vendor assessments, and ensure compliant, scalable data foundations for medical AI solutions.
Requirements
Candidates must hold a Master's degree in computer science, data engineering, or a related field with progressive experience in data architecture and AI platforms. Strong knowledge of healthcare data regulations, modern data platforms, and the ability to influence global cross-functional teams is required.
Key skills
- Data architecture — in 39 other listings on The Stack
- AI development — in 1 other listing on The Stack
- Platform strategy — in 4 other listings on The Stack
- Stakeholder leadership — in 1 other listing on The Stack
- Cloud platforms — in 69 other listings on The Stack
- Data engineering — in 120 other listings on The Stack
- Metadata management — in 4 other listings on The Stack
- Data governance — in 90 other listings on The Stack
- Healthcare data compliance
- Medical imaging
- API development
- Distributed systems
- Platform engineering
- Cybersecurity
- Regulatory compliance
- Project roadmap management
On The Stack (as of 2026-11-05)
- This is GE HEALTHCARE's only listing on The Stack.
- 13 visa-sponsored jobs in Austria on The Stack, posted in the last 60 days.
Frequently asked questions about GE HEALTHCARE
Is this AI Data Architect (f/m/d) role still open?
It was posted on 2026-11-03 and is listed as active on The Stack. Confirm on GE HEALTHCARE's application page before applying.
Does GE HEALTHCARE offer visa sponsorship?
This listing is marked as offering visa sponsorship. Eligibility rules are set by the employer, so check the details on GE HEALTHCARE's site.
Where is this role located?
The listing gives the location as Austria. It is marked on-site.
What skills does this role ask for?
The listing names: Data architecture, AI development, Platform strategy, Stakeholder leadership, Cloud platforms, Data engineering, Metadata management, Data governance, Healthcare data compliance, Medical imaging, API development, Distributed systems, Platform engineering, Cybersecurity, Regulatory compliance, Project roadmap management.