Design, build, and maintain scalable data pipelines (batch and real-time).
Develop production-grade data workflows for healthcare data.
Work with Spark, Databricks, Airflow/Temporal, and dbt to ingest and manage data.
Design reusable data models for analytics and AI/ML use cases.
Ensure platform resiliency with CI/CD, observability, and logging.
Leverage Infrastructure as Code (Terraform, CloudFormation) to manage cloud resources.

🎯 Requirements

Bachelor's or Master's in Computer Science, Engineering, or related field.
8–12 years in software or data engineering with cloud-native data systems.
Healthcare domain software development experience (payers/providers/health tech).
Experience with healthcare data types: FHIR, HL7, Claims, EDI, Epic/Clarity.
Python, SQL, and Apache Spark proficiency.
Azure cloud-native platform experience; IaC with Terraform/CloudFormation.

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