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Qureight seeks a senior clinical data engineer to design and maintain data pipelines that turn messy clinical trial data into analysis-ready datasets, with a focus on healthcare data standards, cloud tools, and close collaboration with data scientists.
The role centers on handling medical imaging data and clinical endpoints with care and regulatory awareness, ensuring data quality to support AI-powered imaging research.
A senior clinical data engineer typically builds and maintains pipelines that turn messy clinical trial data into clean, analysis ready datasets. Strong candidates bring experience with healthcare data standards, cloud data tools, and working closely with data scientists. At a company focused on AI powered imaging for lung and heart trials, the work likely involves handling medical images and clinical endpoints with care and precision.
AI changes this role by automating parts of data cleaning and quality checks, letting engineers focus on pipeline design and data integrity. The human side stays central: understanding clinical context, ensuring regulatory compliance, and making judgment calls when data is ambiguous. This role helps make sure AI models get reliable data, which is still a hands on engineering task.
Working here would give direct experience with AI ready data pipelines for medical imaging and clinical endpoints. That includes learning how to structure data for machine learning models and how to validate outputs in a regulated health setting. Building skills in cloud platforms, data versioning, and clinical data standards would be a natural part of the job.
This is our own read, written from the employer's posting and the company's Spotlight. The employer's posting is the source of truth for the role.
Qureight provides AI-powered imaging and precision endpoints for lung and heart clinical trials, per the company.