We are seeking a seasoned Data Architect / Engineer with over 10 years of experience in designing, building, and managing data pipelines and architectures for medical imaging systems such as CT, MRI, PET, and Ophthalmic modalities. The ideal candidate will have strong expertise in data engineering frameworks, AI/ML integration, and ensure full compliance with DICOM, GxP, and FAIR data principles for high-quality, regulatory-compliant healthcare data workflows.
Design and implement robust data pipelines for medical imaging workflows across CT, MRI, PET, and Ophthalmology modalities.
Develop and maintain ETL frameworks to ingest, transform, and manage structured and unstructured imaging data.
Ensure data quality, integrity, and compliance with standards like DICOM, GxP, and healthcare data governance protocols.
Collaborate with AI/ML teams to enable model integration and training using medical imaging datasets.
Define data modeling, storage, and retrieval strategies supporting scalable data analytics and research.
Implement FAIR (Findable, Accessible, Interoperable, Reusable) data management practices.
Oversee cloud-based data environments (preferably AWS) for performance, cost-efficiency, and compliance.
Work closely with clinical and research teams to ensure accurate and ethical data utilization.
10+ years of experience in data engineering, data architecture, or related fields.
Strong understanding of medical imaging workflows and standards such as DICOM, SDTM, ADaM.
Proven experience in data compliance frameworks (GxP, HIPAA, FAIR data).
Hands-on experience with ETL tools, data orchestration, and pipeline automation.
Strong problem-solving skills and ability to design scalable, compliant data architectures for healthcare analytics.
Prior experience integrating AI/ML models within data pipelines is a strong plus.
Python, SQL, NoSQL, ETL, AWS, Airflow, Spark, DICOM, SDTM, ADaM, GxP, FAIR Data, Data Modeling, Data Warehousing, Cloud Architecture, AI/ML Integration, Medical Imaging Systems (CT, MRI, PET, Ophtha)