Data Engineer

Description

We are looking for a Data Engineer to support the design, development, and optimization of modern data solutions in Philadelphia, Pennsylvania.

This Long-term Contract position focuses on building reliable pipelines and delivering high-quality data for healthcare and regulatory reporting needs.

The ideal candidate brings strong experience with Azure-based data engineering, Python, SQL, and large-scale data processing, with the ability to work across complex clinical and patient-quality datasets.

Responsibilities

• Design and maintain scalable data pipelines that ingest, transform, and deliver data from clinical and operational sources for analytics and reporting.
• Develop data engineering solutions using Azure services, Databricks, Spark, and Python to improve performance, reliability, and maintainability.
• Work with healthcare-related datasets, including patient quality measures, readmissions, vital sign information, and other clinical reporting domains.
• Explore and interpret Epic Clarity tables to identify relevant source data and support accurate downstream consumption.
• Build and optimize ETL workflows that move data across platforms while preserving data integrity and compliance expectations.
• Partner with analysts, reporting teams, and external stakeholders to provide data needed for quality metrics and regulatory submissions.
• Implement data validation and monitoring processes to ensure completeness, consistency, and accuracy across critical datasets.
• Support file-based data exchange and integration processes, including secure FTP-based transfers where required.

Requirements

• Strong hands-on experience in data engineering with deep knowledge of Python or SQL, and preferably strength in both.
• Proven experience working with Azure data platforms, with Azure Databricks strongly preferred.
• Proficiency with distributed data processing technologies such as Apache Spark; experience with Hadoop or Kafka is beneficial.
• Demonstrated background building ETL processes and scalable data pipelines in cloud environments.
• Experience working with healthcare, clinical, patient-quality, or other regulated data domains is highly preferred.
• Familiarity with Epic Clarity and the ability to investigate source tables for reporting and analytics needs.
• Solid understanding of data quality, governance, and compliance considerations in regulated environments.

Technology Doesn't Change the World, People Do.