Should have strong knowledge in GCP BigQuery and SQL.
Should be proficient with Python or R for data analysis.
Should have Strong knowledge and proven experience of data mining algorithms and statistical analysis.
Should have Ability to interpret complex data and present insights clearly.
Responsibilities
• Design and implement robust data pipelines on cloud platforms using Cloud Composer and Cloud Dataproc to process large scale payer domain datasets with high reliability and performance.
• Develop optimized PySpark and Python code to transform cleanse and aggregate complex healthcare data while maintaining strict data quality and accuracy standards.
• Build productive data models and schemas in BigQuery and Cloud SQL that support analytics reporting and downstream applications for payer focused use cases.
• Optimize BigQuery queries and storage strategies to reduce cost improve execution time and enhance user responsiveness for business critical workloads.
• Collaborate with product owners data analysts and business stakeholders from the payer domain to translate analytical needs into scalable technical solutions.
• Implement monitoring alerting and automated recovery for Cloud Composer workflows and data pipelines to ensure stability and predictable operations in day to day execution.
• Apply healthcare payer domain knowledge to design data transformations reference mappings and validation rules that align with regulatory clinical and financial requirements.
• Perform code reviews provide constructive feedback and maintain coding standards to ensure maintainable secure and well documented PySpark and Python solutions.
• Troubleshoot production issues across BigQuery Cloud SQL Cloud Composer and Cloud Dataproc environments to restore serv