Data Engineer (Health Data Metrics)

keeblerhealth; United States; On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Competitive salary

Fast-paced environment

Professional growth

Collaborative culture

Meaningful impact

Job summary

Keebler Health is building the operating system for value-based care and seeks a skilled Data Engineer to lead scalable reporting metrics for healthcare data and AI-driven insights.

The role focuses on data infrastructure powering healthcare AI solutions, with emphasis on quality metrics, population health, and FHIR interoperability. Level and salary will align with experience.

Qualifications

• Proven experience in data engineering with SQL, Python, and AWS.
• Experience with dbt and Spark/PySpark for data transformation.
• Familiarity with healthcare data systems (HEDIS, population health, FHIR).
• Knowledge of data warehousing and workflow orchestration.

Responsibilities

• Design, build, and maintain scalable data pipelines for ETL/ELT on AWS.
• Develop, test, and deploy data transformation and analysis using SQL and Python.
• Implement data warehousing using Redshift Serverless and AWS services.
• Leverage dbt for modeling, transformation, and documentation.
• Use Temporal for pipeline orchestration.

Skills

SQL

Python

AWS

Tools

dbt

Spark/PySpark

Temporal

Terraform

Job description

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.