Data Engineer – Health Data Metrics
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Job Description
Data Engineer building AWS data pipelines and healthcare quality metrics infrastructure for Keebler Health’s value-based care platform. Integrating FHIR, population health, and HIPAA-compliant data systems.
Responsibilities:
- Lead efforts around reporting scalable metrics for healthcare data and AI-driven suggestions
- Design, build, and maintain scalable, efficient ETL/ELT data pipelines on AWS
- Develop, test, and deploy solutions using SQL and Python for data transformation and analysis
- Implement and manage data warehousing solutions using Redshift Serverless and other AWS data services
- Use dbt for data modeling, transformation, and documentation
- Use workflow orchestration tools such as Temporal for pipeline automation
- Work with healthcare quality metrics for value-based care and align data with industry standards
- Integrate population health tools and analytics into data workflows with stakeholders
- Maintain familiarity with FHIR data models and interoperability standards
- Ensure compliance with HIPAA and other healthcare regulations
- Identify and resolve data pipeline performance bottlenecks
- Optimize data storage and query performance in Redshift Serverless and AWS
- Incorporate emerging data engineering and healthcare technology innovations
- Partner with data and engineering teams to ensure data accessibility and business alignment
- Develop scalable solutions integrating complex healthcare datasets while ensuring data quality and accuracy
- Contribute to secure, scalable, and efficient AWS data architecture
Requirements:
- 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 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 Airflow, Dagster, or Temporal
- Hands-on experience with AWS Glue, EMR, Iceberg, Redshift Serverless, S3, Lambda, and related technologies
- Strong experience with 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
- Experience with Infrastructure as Code tools such as Terraform
- Strong problem-solving skills and attention to detail when working with large, complex, and heterogeneous datasets
- Resume and a highly personalized, bold, and hilarious Keebler Health–style introduction required when applying
Benefits:
- Competitive salary and benefits package
- Professional growth and development opportunities
- Collaborative and supportive team culture
- Opportunity to work in a fast-paced, innovative environment
- Chance to make a meaningful impact on the healthcare industry
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