BD APM Data Engineering InternAt — Becton Dickinson

Project Overview

Data Engineering team has developed a cloud-based data infrastructure and data warehousing application for Algorithms Group. We continue to expand clinical data pipeline architecture and clinical databases. Data warehousing capability along with cloud computing infrastructure allows for rapid data processing and algorithm development.

The main goals of this project are to continue expanding and optimizing data ingestion, data standardization, data processing, storage and analytical processes. The Data Engineer Intern will support database architects and data scientists on various analytical initiatives and data processing effort.

Required skills

•  Must be a highly motivated self-starter, proactive and creative in achieving goals; a high-energy individual who has excellent communications, teamwork and partnering skills is required.
•  High proficiency with Matlab and/or Python for data analysis is required.
•  High proficiency with word processing software (Word, PowerPoint, Excel) is required.
•  Experience with Databases is highly preferred.
•  Understanding cardiovascular physiology and hemodynamics is highly preferred.

Tasks:

Develop and optimize Data Analytics, Databases and Cloud Platform to assist Data Scientists in rapid data processing and algorithms development.

Training:

1. Gain knowledge in cardiovascular physiology and functional hemodynamic monitoring from leading scientists.

2. Gain experience in Data Engineering, Databases, ETL processes, Cloud platform

3. Gain experience in Data analysis, processing, and analytics

4. Gain experience in R&D and new product development processes in Edwards Lifesciences with direct exposure to innovative product development projects of advanced hemodynamic monitoring products, including sensors, monitors, signal processing algorithms and software.

Learning Outcome:

1. Work with a team of Data engineers and scientists to design, and implement internal process improvements, automate manual processes, optimizing data delivery, re-designing processes for greater scalability

2. Support clinical data processing and analysis from sites in the US and Europe

3. Brainstorm with other data engineers to perform root cause analysis, on internal and external data, and processes to answer specific business questions and identify opportunities for improvement