Johnson & Johnson is currently seeking a Clinical Data Engineer to join our Biosense Webster team located in Irvine, CA
At Johnson & Johnson, we believe health is everything. Our strength in healthcare innovation empowers us to build a world where complex diseases are prevented, treated, and cured, where treatments are smarter and less invasive, and solutions are personal. Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity. Learn more at https://www.jnj.com/.
For more than 130 years, diversity, equity & inclusion (DEI) has been a part of our cultural fabric at Johnson & Johnson and woven into how we do business every day. Rooted in Our Credo, the values of DEI fuel our pursuit to create a healthier, more equitable world. Our diverse workforce and culture of belonging accelerate innovation to solve the world’s most pressing healthcare challenges.
We know that the success of our business – and our ability to deliver meaningful solutions – depends on how well we understand and meet the diverse needs of the communities we serve. Which is why we foster a culture of inclusion and belonging where all perspectives, abilities and experiences are valued and our people can reach their potential. At Johnson & Johnson, we all belong.
Clinical Data Engineer is responsible for expanding and optimizing device data pipeline architecture, as well as optimizing data flow and collection for cross functional teams. The Data Engineer supports Data Managers, Statisticians, and Data Scientists on data initiatives and will ensure optimal data delivery for ongoing clinical objectives. Must be self-directed and comfortable supporting the data needs of multiple teams, systems, and products. The right candidate will be excited by the prospect of optimizing our data architecture to support our next generation of products and data initiatives and contributes towards the best practices for cloud-based data analytics.
Responsibilities:
- Improve data quality: Implement methods to improve data reliability and quality.
- Convert raw data: Collect, manage, and convert raw data into usable information for data scientists and business analysts to interpret Clinical data.
- Develop database architecture: Develop and maintain the database architecture and data processing systems.
- Test and maintain data infrastructure: Architect, build, test, and maintain the data infrastructure using cloud-based systems.
- Implements the AI/ML models and assists Data Scientists or Statisticians in model fitting or other optimizations related to data quality.
- Work under guidance: mentor junior Data Engineers in best practices and collaborate on complex problem-solving projects.
