Description

You will design and implement data analytics roadmaps and engineering pipelines for healthcare payer platforms.

This role is remote.

Responsibilities

• Design and maintain data pipelines using Python and PySpark to process large volumes of healthcare data.
• Execute complex data analysis projects focused on risk rating, claims adjudication, and enrollment optimization.
• Implement ETL processes to extract, transform, and load data from various sources into target databases.
• Optimize data workflows for performance and scalability, managing ingestion, transformation, and storage in AWS.
• Develop monitoring and alerting mechanisms to proactively address data quality issues and performance bottlenecks.

Required Skills

• Minimum 5 years of experience in healthcare payer analytics and data engineering.
• Expertise in Python programming and hands-on experience with PySpark for data processing.
• Proficiency with big data technologies including Hadoop, Spark, or Scala.
• Experience managing data in AWS services such as S3, Glue, EMR, and Redshift.
• Strong understanding of risk adjustment methodologies, including Hierarchical Condition Category (HCC) coding.
• In-depth knowledge of healthcare claims and enrollment data structures.
• Experience modeling data in relational databases like PostgreSQL and MySQL.

Preferred Skills

• Experience working with large-scale multi-tenant analytics platforms.

Key Skills

Education

Any Gradute