Real-World Data Engineer
We are seeking an experienced Data Engineer to join our long-term global clinical research initiative. This is a fantastic opportunity for a proactive and collaborative individual who is comfortable working in a remote environment.
The role will initially span 6 to 12+ months, but is expected to extend for several years. In this position, you'll support the full lifecycle of real-world clinical and imaging data — from acquisition and quality control to processing and organization — helping to enable data-driven insights for high-impact research programs.
Key Responsibilities:
* Data Ingestion: Collect and ingest large volumes of real-world data (RWD), including medical imaging and related annotations
* Data Quality Control: Perform detailed quality checks to ensure accuracy, completeness, and consistency
* Data Pipelines: Build and maintain data pipelines to structure and prepare complex datasets
* Data Cleaning and Transformation: Clean, transform, and normalize raw data for downstream research analysis
* Collaboration with Data Scientists: Work closely with Data Scientists to prepare specific curated subsets for focused analysis
* Documentation: Document data sources, processing steps, and quality control procedures
Ideal Profile:
* 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
This is a chance to be part of meaningful work with long-term potential. If you're a skilled Data Engineer looking for a challenging opportunity, we encourage you to apply through the link below.