We are seeking a skilled Data Engineer to support the full lifecycle of real-world clinical and imaging data.
This role will involve collecting and ingesting large volumes of data, performing quality checks, and building data pipelines to structure and prepare complex datasets.
Responsibilities:
* Collect and ingest large volumes of real-world data, including medical imaging and related annotations
* Perform detailed quality checks to ensure accuracy, completeness, and consistency
* Build and maintain data pipelines to structure and prepare complex datasets
* Clean, transform, and normalize raw data for downstream research analysis
* Work closely with Data Scientists to prepare specific curated subsets for focused analysis
* Document data sources, processing steps, and quality control procedures
Requirements:
* 3–7 years of experience as a Data Engineer or similar role
* Strong proficiency in Python and SQL
* Experience working with large-scale data pipelines
* Clear and confident communication skills in English (written and verbal)
* Ability to work independently and manage multiple data workflows in parallel
* Self-motivated and eager to work in a fast-paced, research-oriented environment
Nice to Have:
* Experience with medical data, imaging (DICOM), clinical research, or pharmaceutical environments
About the Role:
This is a fantastic opportunity for a Data Engineer who is hands-on, proactive, and comfortable working in a collaborative, remote environment. The role will initially span several months but is expected to extend for several years.
The successful candidate will be able to support the full lifecycle of real-world clinical and imaging data, from acquisition and quality control to processing and organization. This includes collecting and ingesting large volumes of data, performing quality checks, and building data pipelines to structure and prepare complex datasets.
The ideal candidate will have 3–7 years of experience as a Data Engineer or similar role, with strong proficiency in Python and SQL. They will also have experience working with large-scale data pipelines and clear and confident communication skills in English.
In return for their expertise, the successful candidate can expect to work in a fast-paced, research-oriented environment with opportunities for professional growth and development.
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