Data Engineer – Health Data Metrics

This is a fully remote position, open to applicants in United States.

📋 Description

• Spearhead initiatives to report scalable metrics for healthcare data and AI-based recommendations.

• Architect, develop, and sustain efficient ETL/ELT data pipelines on AWS.

• Create, test, and implement solutions utilizing SQL and Python for data transformation and analysis.

• Establish and oversee data warehousing solutions using Redshift Serverless along with various AWS data services.

• Utilize dbt for data modeling, transformation, and comprehensive documentation.

• Employ workflow orchestration tools like Temporal to automate pipelines.

• Collaborate on healthcare quality metrics for value-based care and ensure data alignment with industry standards.

• Incorporate population health tools and analytics into data workflows in partnership with stakeholders.

• Stay updated on FHIR data models and interoperability standards.

• Guarantee compliance with HIPAA and other healthcare regulations.

• Detect and rectify performance bottlenecks in data pipelines.

• Enhance data storage and query performance in Redshift Serverless and AWS.

• Embrace innovative data engineering and healthcare technology advancements.

• Cooperate with data and engineering teams to promote data accessibility and alignment with business goals.

• Create scalable solutions that integrate complex healthcare datasets while maintaining data quality and accuracy.

• Contribute to a secure, scalable, and efficient AWS data architecture.

⛳️ Requirements

• Must be based in the US; applications from foreign candidates will not be considered.

• Demonstrated experience in data engineering roles with proficiency in SQL, Python, and AWS cloud-based data infrastructure.

• Familiarity with dbt and Spark/PySpark for data transformation and modeling.

• Knowledge of healthcare data systems, including HEDIS metrics, population health tools, and FHIR data models.

• Understanding of data warehousing and workflow orchestration tools.

• Strong grasp of healthcare data standards, including FHIR, HL7, and CQL.

• Practical experience in data modeling, normalization, and schema design for intricate datasets.

• Experience in designing and constructing scalable, production-grade data pipelines utilizing Airflow, Dagster, or Temporal.

• Proficient in AWS Glue, EMR, Iceberg, Redshift Serverless, S3, Lambda, and related technologies.

• Solid expertise in dbt, Spark/PySpark, and Pandas.

• Experience in designing and managing HIPAA-compliant data architectures and handling sensitive healthcare data.

• Proven ability to optimize data pipelines for performance, scalability, and reliability in cloud environments.

• Familiarity with Infrastructure as Code tools like Terraform.

• Excellent problem-solving abilities and attention to detail while working with large, complex, and diverse datasets.

• A resume along with a highly personalized, bold, and humorous Keebler Health-style introduction is required when applying.

🏝️ Benefits

• Competitive salary along with a comprehensive benefits package.

• Opportunities for professional growth and development.

• A collaborative and supportive team culture.

• The chance to work in a dynamic, innovative environment.

• An opportunity to make a significant impact on the healthcare sector.