Data Engineer - Quality

** Description*
* Penn Medicine is dedicated to our tripartite mission of providing the highest level of care to patients, conducting innovative research, and educating future leaders in the field of medicine. Working for this leading academic medical center means collaboration with top clinical, technical and business professionals across all disciplines.

Today at Penn Medicine, someone will make a breakthrough. Someone will heal a heart, deliver hopeful news, and give comfort and reassurance. Our employees shape our future each day. Are you living your life's work?

Entity:
Corporate

Department:
PennDnA Data Management & Operations

Location:

3600 Civic Center Blvd. Philadelphia, PA

Hours:

8hr Days (Mostly remote; some in person meetings)

Senior Data Engineer:
PennDnA

Summary:

The Senior Data Engineer will be responsible for designing, developing, and maintaining robust data pipelines, ETL/ELT processes, and other data cleansing and transformation solutions to support data-driven initiatives. This role requires technical expertise in data engineering, database management and cloud technologies, with proven experience in implementing complex data projects in a healthcare or research environment.

Responsibilities

+ Data Integration and Processing:
Design and architect scalable and reliable data pipelines to ingest, process, and transform large volumes of healthcare data from diverse sources, including electronic health records (EHR), clinical systems, research databases, and external data feeds

+ ETL/ELT Development:
Build and optimize ETL/ELT processes and work within Cloud technology such as Azure and Databricks to ensure efficient data extraction, transformation, and loading while maintaining data quality, consistency, and integrity. Collaborate with a variety of stakeholders across the organization to understand data requirements and translate them into effective ETL/ELT solutions that meet organizational goals.

+ Cloud Infrastructure and Technologies:
Implement and maintain cloud-based data platforms and services, leveraging technologies such as AWS, Azure, or Databricks. Design and deploy data solutions using cloud-native services, such as Azure SQL Database, to support advanced analytics, machine learning, and data visualization initiatives.

+ Data Governance and Security:
Enforce data governance policies, standards, and procedures to ensure compliance with regulatory requirements (e.g., HIPAA, GDPR) and organizational data security policies. Participate in implementation of metric standards, access controls, encryption, and auditing mechanisms to protect sensitive healthcare data and ensure data privacy and confidentiality

+ Performance Monitoring:
Monitor performance of data pipelines ETL/ELT processes, databases and data warehouses, troubleshoot issues, and implement optimizations to improve efficiency, reliability, and scalability.

+

Collaboration:

Collaborate with cross-functional teams to define project requirements and develop solutions that meet organizational needs. Provide technical leadership and mentorship to junior data engineers and associate data engineers, fostering a culture of continuous learning and innovation within the data engineering team

+ Continuous Improvement:
Demonstrate a commitment to continuous learning and professional development. Stay current with industry trends, best practices, and emerging technologies in data engineering, ELT/ETL processes and data transformation. Look for opportunities to optimize the team's processes and workflows

+ Performs duties in accordance with Penn Medicine and entity values, policies, and procedures

+ Other duties as assigned to support the unit, department, entity, and health system organization

Credentials:

+ Epic Clarity Data Model (must be completed within 6 months of start date)

Education or Equivalent

Experience:

+ Bachelor of Arts or Science in Computer Science, Information Systems, or related field (Required)

+ 3+ years experience in data engineering, database management, or related roles, with significant experience managing work. Proven track record of leading and executing moderately complex projects with minimal oversight.

Data Engineer:
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