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The role involves developing and maintaining scalable data pipelines and cloud-native applications to support clinical workflows and internal operations. You will collaborate with cross-functional teams to ensure data accuracy and reliability while participating in engineering on-call rotations.
BioIntelliSense is ushering in a new era of continuous health monitoring and clinical intelligence for Remote Patient Monitoring (RPM) and Screening (COVID-19/Infection). Our medical-grade Data-as-a-Service (DaaS) platform seamlessly captures multi-parameter vital signs, physiological biometrics and symptomatic events through an effortless patient experience. The FDA-cleared BioSticker™ and BioButton™ devices make remote monitoring and early detection simple. Through the platform’s advanced analytics, clinicians, patients, and employers will now have access to high-resolution patient trending and reporting to enable medical grade care at home, and medical grade screening in the office, school, or residence. For more information on how BioIntelliSense is redefining remote patient monitoring through medical-grade and cost-effective data services, please visit our website at BioIntelliSense.com.
\nThe Data Engineering team plays a pivotal role in creating, maintaining and developing BioIntelliSense’s data platform for both internal and external facing applications. The team focuses on enterprise data management and data accuracy to support internal operations, R&D teams as well as external operational metrics dashboards. In this role, you will have the opportunity to collaborate with cross-functional teams such as clinical applications, cloud infrastructure, sustaining, and data science, building your analytical mindset and the ability to communicate system-level relationships clearly. You will work primarily with the Python tech stack on Databricks and AWS. Your contributions will have a meaningful impact in BioIntelliSense’s mission to improve patient care around the world.
The role will:
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