Description

Lead the development and implementation of a strategic data analytics roadmap for healthcare payer operations.

Responsibilities

• Design, develop, and maintain data pipelines using Python and PySpark to process large-scale healthcare data within a multi-tenant platform.
• Build and optimize ETL processes to extract, transform, and load data from various sources into target databases.
• Implement data ingestion, transformation, and storage workflows using AWS services including S3, Glue, EMR, and Redshift.
• Model data in relational databases such as PostgreSQL and MySQL to support complex processing requirements.
• Develop monitoring and alerting mechanisms to identify data quality issues and performance bottlenecks.

Required Skills

• 5+ years of experience in healthcare data analytics, specifically within health insurance payers, hospitals, or managed care organizations.
• Proficiency in Python, Scala, R, or PySpark for data manipulation and analysis.
• Hands-on experience with big data technologies including Hadoop and Spark.
• Experience working with cloud platforms, specifically AWS (S3, Glue, EMR, Redshift).
• Strong command of SQL and relational database modeling (PostgreSQL, MySQL).
• Deep understanding of risk adjustment methodologies, such as HCC coding, and their impact on reimbursement.
• In-depth knowledge of healthcare claims, enrollment data structures, and HIPAA/CMS compliance requirements.
• Experience with healthcare quality metrics, revenue cycle management, and financial analysis principles.
• Ability to work with electronic health records (EHRs) and health information exchanges (HIEs).

Key Skills

Education

Any Graduate