As a Data Engineer, you will play a crucial role in supporting the full lifecycle of real-world clinical and imaging data. This includes acquisition, quality control, processing, and organization to enable data-driven insights for high-impact research programs.
The ideal candidate will have 3–7 years of experience as a Data Engineer or similar role, with strong proficiency in Python and SQL. You will work closely with Data Scientists to prepare specific curated subsets for focused analysis.
Your responsibilities will include:
* Collecting and ingesting large volumes of real-world data (RWD), including medical imaging and related annotations
* Performing detailed quality checks to ensure accuracy, completeness, and consistency
* Building and maintaining data pipelines to structure and prepare complex datasets
* Cleaning, transforming, and normalizing raw data for downstream research analysis
You will also be responsible for documenting data sources, processing steps, and quality control procedures.
We are looking for someone who is self-motivated, eager to work in a fast-paced, research-oriented environment, and able to work independently and manage multiple data workflows in parallel.
A strong understanding of medical data, imaging (DICOM), clinical research, or pharmaceutical environments is highly desirable but not required.
This is an excellent opportunity to be part of meaningful work with long-term potential.