Data Engineer- PennDnA- Quality (Mid level/Senior)

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)

Summary:

This position is posted at two levels based on experience:

• Data Engineer- PennDnA
• Senior Data Engineer- PennDnA

Candidates will be aligned to the appropriate level based on experience and qualifications.

Data Engineer PennDnA:

The Data Engineer Penn DnA works as part of a team to design, develop, and maintain robust data pipelines, ETL/ELT processes, and data transformation solutions. This role requires technical expertise in data engineering and a commitment to delivering high-quality work products in a timely manner.

Responsibilities

• Data Integration and Processing: Design, develop, and implement scalable data pipelines to ingest, process, and transform diverse datasets from various sources including electronic health records (EHR), clinical systems, research databases, and external sources.
• ETL/ELT Development: Build and optimize ETL/ELT processes and work within Cloud technology such as AWS, Azure and/or Databricks to ensure efficient data extraction, transformation, and loading while maintaining data quality, consistency, and integrity. Collaborate with stakeholders to understand data requirements and translate them into effective ETL/ELT solutions.
• Data Quality Management: Perform data cleansing, transformation, and validation to ensure data accuracy and integrity. Execute troubleshooting and resolving data-related issues and challenges. Implement data governance best practices to ensure compliance with regulatory requirements and institutional policies related to data privacy, security, and confidentiality.
• Performance Monitoring: Monitor performance of data pipelines and ETL/ELT processes, troubleshoot issues, and implement optimizations to improve efficiency, reliability, and scalability.
• Documentation: Develop and maintain documentation for data pipelines, ETL/ELT workflows, and data transformation processes to facilitate knowledge sharing and ensure reproducibility.
• Collaboration: Collaborate with cross-functional teams to understand project requirements and develop solutions that meet organizational needs. Provide regular project updates to team members and stakeholders. Foster professional relationships with colleagues and contribute to a collaborative work environment.
• Continuous Improvement: Demonstrate a commitment to continuous learning and professional development. Look for opportunities to optimize ETL/ELT, data governance and transformation, and troubleshooting 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's Degree Computer Science, Information Systems, or related field Or 4+ years Related experience
• 2+ years Experience in data engineering, utilizing programming skills to build robust data pipelines and dynamic systems. Proven track record of managing and executing projects with minimal oversight. Understanding of SLDC processes including CI/CD approaches.
• 1+ years Experience working with data from Electronic Health Records (EHRs) preferred.

Senior Data Engineer: PennDnA

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.

We believe that the best care for our patients starts with the best care for our employees. Our employee benefits programs help our employees get healthy and stay healthy. We offer a comprehensive compensation and benefits program that includes one of the finest prepaid tuition assistance programs in the region. Penn Medicine employees are actively engaged and committed to our mission. Together we will continue to make medical advances that help people live longer, healthier lives.

Live Your Life's Work

We are an Equal Opportunity employer. Candidates are considered for employment without regard to race, ethnicity, color, sex, sexual orientation, gender identity, religion, national origin, ancestry, age, disability, marital status, familial status, genetic information, domestic or sexual violence victim status, citizenship status, military status, status as a protected veteran or any other status protected by applicable law.