Data Engineer

• Design, develop, and maintain robust data pipelines that move information from healthcare platforms and related source systems into analytics and reporting environments.

• Prepare, standardize, and validate data from claims, clinical records, and social determinants of health sources to ensure accuracy and usability.

• Apply sound data modeling practices to organize information for warehousing, business intelligence, and advanced analytical use cases.

• Build scalable processing solutions using tools such as Python, Apache Spark, Hadoop, and Kafka to support high-volume data operations.

• Partner with analytics, clinical, and business stakeholders to deliver reliable datasets that power descriptive, predictive, and prescriptive insights.

• Monitor pipeline performance, troubleshoot data issues, and improve the reliability and efficiency of end-to-end ETL processes.

• Support the full lifecycle of data initiatives, from source integration and transformation through delivery for reporting and analytical applications. Requirements * Extensive experience in data engineering, with a strong focus on building and supporting enterprise data pipelines.

• Hands-on proficiency with Python for data processing, automation, and pipeline development.

• Experience working with Apache Spark and Hadoop in large-scale data environments.

• Familiarity with Apache Kafka or similar streaming technologies for data movement and integration.

• Strong understanding of ETL development, including extraction, transformation, validation, and loading of complex datasets.

• Knowledge of data warehousing concepts and data modeling best practices.

• Ability to work with healthcare-related data such as claims, clinical, or social determinants of health information.

• Comfortable collaborating in a fast-paced environment where data solutions support operational and clinical outcomes. Technology Doesn’t Change the World, People Do.®

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