Scripps Health
Data Engineer
Scripps Health, San Diego, California, United States, 92189
This is a full time, salaried position, generally Monday through Friday. This is a work-from-home position, but does require residency within the San Diego area.
Join the Scripps Health team and work alongside passionate caregivers to provide patient-centered healthcare. Receive endless appreciation while you build a rewarding career with one of the most respected healthcare organizations nationwide.
Why join Scripps Health?
Selected as one of the 100 Best Places to Work for 2024 by Fortune Magazine and the Great Place to Work Institute for the 16th time. A remarkable achievement as only five healthcare organizations nationwide made the list, and Scripps is the sole healthcare provider in California to be recognized.
Recognized by Newsweek as one of America’s Greatest Workplaces for Diversity in 2024.
Nearly a quarter of our employees have been with Scripps Health for over 10 years.
Ranked 78th in 2023 PEOPLE Companies that Care.
Ranked 95th in Fortune 100 Best Companies to Work for 2023.
Why join this team?
The data engineer will have the unique opportunity to be at the forefront in leveraging new technologies at Scripps Health. Primarily supporting the research department, the data engineer will be able to do more advanced analytical and experimental work, including conversational AI. This person will be joining a tenured team of 6 other data engineers who all share a passion for what they do.
Responsibilities include:
Design and build scalable data pipelines that can extract, transform and load data from cloud and on-premise data sources using SQL and Cloud Big Data technologies, Snowflake and Azure, technologies for business/operational use cases and data governance.
Develop and maintain data pipelines including solutions for data collection, management, metadata and usage.
Work closely with Research Data Scientists and Analytics Developers to optimize and reengineer model code to be modular, efficient and scalable, and to deploy models to production.
Identify, design, and implement internal process improvements: automating manual processes, debug long running and inefficient pipelines, re-design infrastructure for greater scalability, monitor, capture & analyze pipeline metadata and usage.
Develop end-to-end solutions for enterprise strategic initiatives and performance improvement.
Manage, execute and monitor weekly and monthly production operations; resolve and escalate production issues as appropriate.
Partner with business stakeholders to understand business and technical requirements, plan and execute projects, and communicate status, risks and issues.
Perform root cause analysis of system and data issues and develop solutions as required.
Mentor analytics developers / lead on projects.
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Join the Scripps Health team and work alongside passionate caregivers to provide patient-centered healthcare. Receive endless appreciation while you build a rewarding career with one of the most respected healthcare organizations nationwide.
Why join Scripps Health?
Selected as one of the 100 Best Places to Work for 2024 by Fortune Magazine and the Great Place to Work Institute for the 16th time. A remarkable achievement as only five healthcare organizations nationwide made the list, and Scripps is the sole healthcare provider in California to be recognized.
Recognized by Newsweek as one of America’s Greatest Workplaces for Diversity in 2024.
Nearly a quarter of our employees have been with Scripps Health for over 10 years.
Ranked 78th in 2023 PEOPLE Companies that Care.
Ranked 95th in Fortune 100 Best Companies to Work for 2023.
Why join this team?
The data engineer will have the unique opportunity to be at the forefront in leveraging new technologies at Scripps Health. Primarily supporting the research department, the data engineer will be able to do more advanced analytical and experimental work, including conversational AI. This person will be joining a tenured team of 6 other data engineers who all share a passion for what they do.
Responsibilities include:
Design and build scalable data pipelines that can extract, transform and load data from cloud and on-premise data sources using SQL and Cloud Big Data technologies, Snowflake and Azure, technologies for business/operational use cases and data governance.
Develop and maintain data pipelines including solutions for data collection, management, metadata and usage.
Work closely with Research Data Scientists and Analytics Developers to optimize and reengineer model code to be modular, efficient and scalable, and to deploy models to production.
Identify, design, and implement internal process improvements: automating manual processes, debug long running and inefficient pipelines, re-design infrastructure for greater scalability, monitor, capture & analyze pipeline metadata and usage.
Develop end-to-end solutions for enterprise strategic initiatives and performance improvement.
Manage, execute and monitor weekly and monthly production operations; resolve and escalate production issues as appropriate.
Partner with business stakeholders to understand business and technical requirements, plan and execute projects, and communicate status, risks and issues.
Perform root cause analysis of system and data issues and develop solutions as required.
Mentor analytics developers / lead on projects.
#J-18808-Ljbffr