Data Engineer; Health Data Metrics

About this position About Keebler Health

Keebler Health is building the operating system for value-based care. Our mission is to help risk-bearing healthcare organizations thrive in value-based arrangements by unlocking the full power of their data. We empower leading primary care groups, ACOs, and health plans to act on real-time insights that improve outcomes, reduce costs, and fuel sustainable growth.

We're a fast-moving, high-performing team, and we’re looking for people who share our bias toward speed, urgency, and excellence. We are seeking a Data Engineer to lead our efforts around reporting scalable metrics for healthcare data and AI driven suggestions.

We are seeking a skilled and motivated mid level to senior level Data Engineer to join our team and play a critical role in building and optimizing the data infrastructure that powers our healthcare AI solutions. The ideal candidate will bring expertise in modern data engineering tools and techniques, with a specific focus on healthcare quality metrics, population health, and data interoperability standards such as FHIR.

Level and salary will commensurate with experience.

• Design, build, and maintain scalable, efficient data pipelines for ETL/EL T processes on AWS.
• Develop, test, and deploy robust solutions using SQL and Python for data transformation and analysis.
• Implement and manage data warehousing solutions using Redshift Serverless and other AWS data services.
• Leverage dbt (Data Build Tool) for data modeling, transformation, and documentation.
• Utilize workflow orchestration tools such as Temporal for pipeline automation.
• Work with healthcare quality metrics such for value-based care and ensure data alignment with industry standards.
• Collaborate with stakeholders to integrate population health tools and analytics into data workflows.
• Develop and maintain familiarity with FHIR data models and healthcare interoperability standards for seamless integration of healthcare data sources.
• Ensure compliance with HIPAA and other healthcare regulatory requirements in all data handling processes.

• Identify and resolve performance bottlenecks in data pipelines, ensuring high availability and reliability.
• Optimize data storage and querying performance within Redshift Serverless and AWS infrastructure.
• Stay current with emerging trends in data engineering and healthcare technology, incorporating innovations into the data ecosystem.

• Partner with data and engineering teams to ensure data is accessible and meets business requirements.
• Develop scalable solutions for integrating complex healthcare datasets, ensuring data quality and accuracy.
• Contribute to the design and implementation of secure, scalable, and efficient data architecture on AWS.

• Must be US based. No foreign applicants will be considered.
• Proven experience in data engineering roles with expertise in SQL, Python, and AWS cloud-based data infrastructure.
• Experience with tools like dbt and Spark/PySpark for data transformation and modeling.
• Familiarity with healthcare data systems, including HEDIS metrics, population health tools, and FHIR data models.
• Knowledge of data warehousing and workflow orchestration tools.

• Strong understanding of healthcare data standards, including FHIR, HL7 and CQL.
• Hands‑on experience with data modeling, normalization, and schema design for complex datasets.
• Experience designing and building scalable, production‑grade data pipelines using orchestration tools such as Airflow, Dagster, or Temporal.
• Hands‑on experience with AWS data and compute services, including Glue, EMR, Iceberg, Redshift Serverless, S3, Lambda, and related…