Unlocking Meaningful Insights with Data Engineering Expertise
The role of a Data Engineer is pivotal in unlocking the potential of real-world clinical and imaging data.
In this position, you'll be responsible for supporting 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.
You will collect and ingest large volumes of real-world data (RWD), including medical imaging and related annotations. Your attention to detail will ensure accuracy, completeness, and consistency of the data through thorough quality checks.
Beyond data collection and quality assurance, your responsibilities will include building and maintaining data pipelines to structure and prepare complex datasets. You'll also clean, transform, and normalize raw data for downstream research analysis.
Effective collaboration with Data Scientists is essential, as you'll work together to prepare specific curated subsets for focused analysis. Documenting data sources, processing steps, and quality control procedures is crucial for transparency and reproducibility.
This position requires strong proficiency in Python and SQL, as well as experience working with large-scale data pipelines. Clear and confident communication skills in English are necessary for success in this role. Self-motivation and the ability to work independently, managing multiple data workflows in parallel, are also key attributes.
A background in medical data, imaging (DICOM), clinical research, or pharmaceutical environments is not mandatory but would be beneficial in this role. The opportunity to work remotely in an environment that values independence and agility makes this a compelling choice for candidates seeking a dynamic work setting.
This role presents a chance to contribute to meaningful work with long-term potential, making it an attractive option for those eager to make a lasting impact in their career.