Imaging Data Engineer/Architect

We're seeking a highly skilled and experienced Imaging Data Engineer/Architect to join our team, focusing on the critical area of medical imaging within the life sciences and healthcare domain. In this role, you will be instrumental in designing, building, and managing robust data pipelines and architectures for handling vast amounts of imaging data, including radiology and digital pathology. Your expertise will directly contribute to the development and deployment of cutting-edge AI/ML solutions that enhance diagnostic capabilities and patient care.

• Design, develop, and maintain scalable and secure data architectures for large-scale medical imaging datasets (e.g., DICOM, whole slide images).
• Implement and optimize data ingestion, storage, processing, and retrieval mechanisms for imaging data, ensuring data quality, integrity, and compliance with industry standards (e.g., HIPAA, GDPR).
• Collaborate with data scientists and AI/ML engineers to facilitate efficient data access and preparation for model training, validation, and deployment.
• Develop and manage metadata strategies for imaging data, including clinical data integration, to enrich datasets and improve model performance.
• Work with various imaging modalities and understand their specific data characteristics and challenges.
• Ensure the integration of imaging data with other clinical data sources to provide a comprehensive view for analytical and AI applications.
• Implement and maintain data governance policies and procedures for imaging data, ensuring security, privacy, and regulatory compliance.
• Stay abreast of emerging technologies and best practices in big data, cloud computing, and medical imaging.

• Bachelor's or Master's degree in Computer Science, Biomedical Engineering, Electrical Engineering, or a related quantitative field.
• Proven experience as a Data Engineer or Architect, specifically with large-scale imaging datasets in the healthcare or life sciences industry.
• Strong understanding of radiology and digital pathology workflows, data types, and associated clinical metadata.
• Proficiency in programming languages such as Python, Java, or Scala.
• Extensive experience with big data technologies (e.g., Spark, Hadoop, Kafka) and cloud platforms (AWS, Azure, Google Cloud Platform).
• Familiarity with medical imaging standards and formats (e.g., DICOM, NIfTI, TIFF).
• Experience with computer vision libraries and frameworks (e.g., OpenCV, scikit-image, TensorFlow, PyTorch) for image processing, feature extraction, and analysis.
• Understanding of image segmentation, object detection, and classification techniques.
• Knowledge of distributed computing for image processing workloads.
• Experience with database systems (SQL and NoSQL).
• Excellent problem-solving skills and the ability to work independently and as part of a team.
• Strong communication and interpersonal skills.