Spring House, Pennsylvania, United States of America
Base: $117,000 to $201,250; bonus/equity: eligible...
Fully remote
Data pipelines for oncology r&d data
Python, r, and sql for data processing
Cloud-based technology platform (aws)
Support how we advance data capture, build and optimize data workflows and store data by designing and implementing engineering requirements, focusing on applications in Oncology R&D
Job Summary
Support how we advance data capture, build and optimize data workflows and store data by designing and implementing engineering requirements, focusing on applications in Oncology R&D.
Serve as both a people leader and a hands-on contributor for designing, developing and maintaining data pipelines for acquiring, managing and storing Oncology R&D data from diverse sources.
Leverage cloud-based technology platforms to accomplish goals, such as building and maintaining data repositories using AWS S3, and create and optimize data flows for structured and unstructured data.
Matching Summary
Support how we advance data capture, build and optimize data workflows and store data by designing and implementing engineering requirements, focusing on applications in Oncology R&D.
Salary
Base: $117,000 to $201,250; Bonus/Equity: Eligible for annual performance bonus; Benefits: Medical, dental, vision, life insurance, disability, retirement plan, savings plan, paid time off
Skills & Requirements
Must-have
Data pipelines for Oncology R&D data
Python, R, and SQL for data processing
Cloud-based technology platform (AWS)
Data versioning and lineage tracking
Software development best practices (DevOps)
Nice-to-have
Healthcare data standards experience
High dimensional data handling
Machine learning operations (MLOps)
Key Requirements
5+ years of experience in data engineering
2+ years experience managing a technical team
Advanced degree (Master’s or equivalent) preferred
Proficiency in data engineering tools and cloud architecture
Experience with unstructured and other database types