AWS Big Data Engineer

Required Skills & Experience
Need 8+ years of overall IT experience with a strong focus on Data Engineering, preferably within healthcare, life sciences, or payer/provider environments. 
Minimum 5+ years of hands-on experience designing and building scalable data pipelines supporting clinical, claims, and operational data. 
Strong understanding of healthcare data models and standards, including FHIR (Fast Healthcare Interoperability Resources), HL7 v2/v3, and EDI (X12 – 837/835). 
Expertise in modern data architecture patterns such as Data Lakes, Data Warehouses, and Lakehouse architectures, with exposure to Healthcare Data Platforms. 
Hands-on experience with AWS cloud services including S3, Glue, EMR, Redshift, Lambda, Step Functions, and HealthLake (preferred). 
Proficiency in Apache Spark (PySpark/Scala) for processing large-scale structured and unstructured healthcare datasets (EHR, EMR, claims, etc.). 
Strong programming skills in Python and/or Scala, along with advanced SQL for data transformation, validation, and performance optimization.