Data Engineer PennDnA (Mid and Senior) (Hybrid)

Entity: Corporate

Department: PennDNA Data Mgmt and Ops

Location: 3600 Civic Center Blvd. 

Hours: 8hr days(Hybrid)

PennDnA (Data and Analytics) is an enterprise wide group centered on Decision Support, Data Access, and Data Visualization. Our team of experienced personnel is responsible for guiding customers through the challenges of requirements gathering and decision making and on to the realized end-product – whether this is a complete enterprise dashboard solution, additions to our data warehouse(s), or an ad-hoc report request. PennDnA leverages Penn's massive stores of data to help everyone from corporate administration to researchers make better decisions to achieve all three missions of Penn Medicine.

Penn Medicine's Abramson Cancer Center (ACC) is a world leader in cancer research, patient care, and education. The ACC's Oncology Informatics Program is dedicated to unlocking the power of information technology to improve cancer care and research. Led by the Chief Oncology Informatics Officer, the Program envisions a technology-enabled learning cancer center leading the world in continuous quality improvement, discovery, and innovation.

The Senior Data Engineer is positioned within PennDnA and dedicated to supporting the ACC’s data assets and solutions.

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

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.
  
• 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.
  
• 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.
  
• 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
  

Education & Experience:

Data Engineer:

• Bachelors Degree in Computer Science, Information Systems or related field
• OR 4+ years of related experience
• AND 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:

• Bachelors Degree in Computer Science, Information Systems or related field
• And 3+ years of 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.
• Epic Clarity Data Model (must be completed within 6 months of start date)