Keebler Health is an AI-first risk adjustment platform for providers and payers that are at risk for Medicare & Medicaid lives.  Through a custom-built, transformer AI model, Keebler Health quickly uncovers risk adjustment opportunities with minimal encounter data.

Keebler Health

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.

About The Role

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.

Key Responsibilities

Data Engineering and Development

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.

Healthcare Data Expertise

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.

Optimization and Innovation

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.

Collaboration and Impact

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.

Required Qualifications

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.

Preferred Skills

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 technologies.Strong experience with data transformation and distributed processing, using tools such as dbt, Spark/PySpark, and Pandas.Experience designing and operating HIPAA-compliant data architectures and handling sensitive healthcare data.Demonstrated ability to optimize data pipelines for performance, scalability, and reliability in cloud environments.Strong problem-solving skills and attention to detail when working with large, complex, and heterogeneous datasets.Experience with Infrastructure as Code (IaC) tools such as Terraform.

What We Offer

Competitive salary and benefits package.Opportunity to work in a fast-paced, innovative environment.Professional growth and development opportunities.Collaborative and supportive team culture.Chance to make a meaningful impact on the healthcare industry.

When applying

In Addition To Your Resume, Also Include

A highly personalized, bold, and hilarious “Keebler Health–style” introduction that grabs attention - outgoing, fun, and uniquely you (not uniquely ChatGPT). Think: confident, high-energy, slightly irreverent (but still professional), with a smart nod to healthcare, value-based care, and the fact that we’re building something real.

Data Engineer (Health Data Metrics)

What the job involves