Senior Consultant - Healthcare Data Engineering & Digital Health Consulting (Germany / EU) Job Summary

At EY, you ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all.

The Opportunity

As a Senior Consultant within EY s Digital Health Excellence Center (DHEC), you will support healthcare organizations, public administrations, providers, and digital health stakeholders across Germany and the EU in building scalable, secure, and interoperable data platforms. You will combine healthcare domain understanding, data engineering expertise, and consulting skills to design, implement, and operationalize modern data solutions that support AI, analytics, interoperability, and digital health transformation.

Key Responsibilities

- Healthcare Data Engineering & Consulting
- Advise healthcare clients on modern data engineering approaches, data platform modernization, and digital health transformation initiatives.
- Analyze and interpret healthcare-related data such as electronic health records, medical imaging data, wearables, clinical studies, and operational datasets to identify patterns, trends, and improvement opportunities.
- Translate business, clinical, and technical requirements into scalable data engineering solutions that improve patient and healthcare skilled experiences.
- Support client workshops, requirements gathering, solution design, and implementation planning across healthcare data programs.

- Data Pipelines, Platforms & Cloud Architecture

- Design, build, and maintain databases, data pipelines, and cloud-based data architectures to support AI, analytics, and digital health initiatives.
- Develop scalable and secure ETL/ELT pipelines that integrate structured and unstructured healthcare data from multiple clinical and administrative sources.
- Ensure data integrity, quality, scalability, performance, and security across healthcare data platforms.




- Work with cloud platforms such as Azure, AWS, and GCP to enable modern healthcare data ecosystems.

- AI, Machine Learning & MLOps Enablement

- Support the development, implementation, and integration of machine learning models and LLM applications into production healthcare environments.
- Collaborate with MLOps, DevOps, IT, and clinical teams to operationalize AI-enabled healthcare solutions.
- Apply CI/CD, containerization, and deployment practices using tools such as Kubernetes and Docker.
- Enable data foundations required for advanced analytics, AI use cases, and healthcare decision support.

- Healthcare Interoperability & Data Standards

- Apply healthcare interoperability standards and data models including HL7, FHIR, openEHR, SNOMED CT, OMOP, IHE, and xDT.
- Support integration of healthcare data across EHRs, clinical systems, research platforms, data repositories, and digital health applications.
- Collaborate with technical and clinical stakeholders to identify information gaps and improve data exchange across systems.

- Regulatory, Privacy & Compliance

- Ensure solutions comply with GDPR, clinical study requirements, healthcare data protection standards, and applicable EU regulatory expectations.
- Embed security, privacy, and compliance considerations into data engineering design and delivery.
- Support clients in managing regulatory and industry-specific requirements for healthcare data platforms.

- Project Delivery & Stakeholder Collaboration

- Lead or support data engineering workstreams within complex digital health transformation programs.
- Collaborate with technical, clinical, data science, and business teams to optimize processes and close information gaps.




- Support business development through technical expertise in healthcare data science and data engineering.
- Mentor junior team members and contribute to capability development within the Digital Health Excellence Center.

Experience & Qualifications Required Experience
- 4-7 years of relevant experience in data engineering, data science, healthcare IT, digital health, cloud data platforms, or related consulting roles.
- Experience designing, building, and maintaining healthcare data pipelines, databases, and cloud architectures.
- Experience working with multidisciplinary teams across business, technology, clinical, data science, and IT functions.
- Exposure to healthcare, clinical data, public sector health, or regulated data environments is preferred.

Technical Expertise
- Programming and analytics: Python, R, SQL, statistics, and data analysis.
- Cloud computing: Azure, AWS, or GCP.
- MLOps/CI/CD: Kubernetes, Docker, deployment pipelines, and production integration concepts.
- Data engineering: databases, data pipelines, ETL/ELT, data quality, and scalable data architecture.
- Healthcare interoperability: HL7, FHIR, openEHR, SNOMED CT, OMOP, IHE, and xDT.
- Regulatory and compliance: GDPR, clinical studies, healthcare data protection, and industry-specific requirements.

Education
- Bachelor's or Master's degree in Computer Science, Data Science, Health Informatics, Medical Informatics, Engineering, Mathematics, Information Systems, or a related field.

Languages
- German: C1 or above.
- English: C1 or above.

What We Look For
- Strong analytical, problem-solving, and critical thinking skills.
- Ability to communicate technical concepts clearly to healthcare, business, and executive stakeholders.
- Consulting mindset with strong client-service orientation and structured delivery approach.
- Agile, curious, and team-oriented approach.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

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