Enterprise Data Systems Engineer Senior, FT, Variable

Prisma Health•Greenville, SC

About The Position

Inspire health. Serve with compassion. Be the difference. Job Summary Plays a pivotal role in designing, developing, and implementing complex data solutions that empower our organization with transformative data-driven insights. Leverages expertise in data engineering, system integration, and healthcare data to build and manage a robust and scalable data infrastructure that supports Prisma Health, the clinically integrated network, and health plan. Provides mentorship and guidance to junior engineers, fostering a strong data engineering team. Essential Functions All team members are expected to be knowledgeable and compliant with Prisma Health's values: Inspire health. Serve with compassion. Be the difference. Lead the design, development, and implementation of complex data pipelines for efficient data ingestion, transformation, and loading (ETL) across various hospital systems Collaborate with data architects, analysts, and stakeholders to understand data requirements, translate them into technical specifications, and define data governance strategies Lead the integration of disparate data sources from Electronic Health Records (EHR), administrative systems, and clinical applications, ensuring data quality and consistency. Design and implement robust data quality checks and monitoring processes to ensure data pipelines meet high standards. Develop and maintain automated data processing tasks using scripting languages (e.g., Python, Shell). Architect and manage data lakes, warehouses, and other data storage solutions, considering scalability and performance optimization. Partner with system administrators to ensure secure and highly available data infrastructure. Troubleshoot and resolve complex data integration and processing issues, providing root cause analysis and solutions. Mentor and guide junior data engineers, fostering a collaborative and high-performing team environment. Document data pipelines, workflows, and processes for future reference and knowledge transfer. Stay current on the latest data engineering tools and technologies. Performs other duties as assigned.

Requirements

Education - Bachelor's degree in Information Technology or a related field of study.
Experience - Five (5) years of Computer science, bioinformatics, management information science, or database administration, with a strong preference for candidates with experience in healthcare data environments.
In-depth experience with data warehousing and data lake architectures.
Strong understanding of data ETL processes, data quality principles, and data governance best practices.
Expertise in scripting languages for data manipulation and automation (e.g., Python, Shell).
Extensive experience with data integration tools and technologies (e.g., ETL tools, APIs).
Experience working in a Linux/Unix environment.
Excellent analytical and problem-solving skills.
Strong communication, collaboration, and leadership skills

Nice To Haves

Master's degree preferred.
Experience with cloud-based data platforms (e.g. Snowflake).

Responsibilities

Lead the design, development, and implementation of complex data pipelines for efficient data ingestion, transformation, and loading (ETL) across various hospital systems
Collaborate with data architects, analysts, and stakeholders to understand data requirements, translate them into technical specifications, and define data governance strategies
Lead the integration of disparate data sources from Electronic Health Records (EHR), administrative systems, and clinical applications, ensuring data quality and consistency.
Design and implement robust data quality checks and monitoring processes to ensure data pipelines meet high standards.
Develop and maintain automated data processing tasks using scripting languages (e.g., Python, Shell).
Architect and manage data lakes, warehouses, and other data storage solutions, considering scalability and performance optimization.
Partner with system administrators to ensure secure and highly available data infrastructure.
Troubleshoot and resolve complex data integration and processing issues, providing root cause analysis and solutions.
Mentor and guide junior data engineers, fostering a collaborative and high-performing team environment.
Document data pipelines, workflows, and processes for future reference and knowledge transfer.
Stay current on the latest data engineering tools and technologies.
Performs other duties as assigned.