GCP Developer

AIA - Kochi | Weekend Drive - In Person | 25th Sep 2026

Skill: GCP, BigQuery, Python

Experience : 6 - 8 Years

Job Summary

GCP Data Engineer

Requirement for N & P program .

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 robust data pipelines using Cloud Composer and PySpark to process payer data at scale and ensure timely availability of curated datasets for analytics consumers in day shift operations.
• Develop efficient data models in BigQuery and Cloud SQL that support complex payer reporting needs such as claims analysis utilization trends and cost optimization while maintaining high query performance.
• Implement data ingestion frameworks in Python to integrate diverse payer data sources including claims eligibility provider and reference data into Cloud Dataproc based processing workflows.
• Optimize PySpark and SQL transformations to reduce processing time and compute costs while preserving accuracy of key payer metrics and regulatory reporting fields.
• Build modular reusable code components for data validation cleansing and enrichment in Python so that payer data assets remain consistent reliable and ready for downstream consumption.
• Configure Cloud Composer workflows to orchestrate multi step data jobs across BigQuery Cloud SQL and Cloud Dataproc with clear monitoring and alerting for operational stability.
• Apply payer domain understanding to translate business rules such as benefit structures member attribution and claim adjudication logic into precise data transformations.
• Collaborate with product owners data analysts and actuaries to refine requirements and deliver data solutions that enable improved payer decision making and member service quality.
• Implement strong data quality checks and reconciliation processes that identify anomalies in payer datasets and prevent inaccurate insights from reaching business users.
• Ensure compliance with healthcare privacy regulations by applying appropriate data masking access controls and auditing across Cloud SQL BigQuery and related data services.
• Document technical designs data flow diagrams and transformation logic in a clear way that supports maintainability onboarding and future enhancements in a hybrid work environment.
• Troubleshoot production incidents in day shift and perform root cause analysis to prevent recurrence while communicating resolution steps to relevant stakeholders.
• Continuously evaluate new cloud features and data engineering practices that could improve performance resilience and value of payer data platforms.
  
  

Qualifications

• Show proven experience of six to ten years in data engineering or development roles using Cloud SQL BigQuery Cloud Composer Cloud Dataproc PySpark and Python for large scale data projects.
• Demonstrate strong proficiency in writing optimized SQL PySpark jobs and Python scripts with a focus on reliability reusability and cost efficient execution.
• Exhibit solid understanding of payer concepts such as claims lifecycle member enrollment provider networks and reimbursement methodologies and reflect this in technical solutions.
• Display experience working in hybrid work models that require effective remote collaboration clear documentation and proactive communication across distributed teams.
• Show familiarity with data warehousing dimensional modeling and analytical reporting patterns tailored specifically for payer and broader healthcare analytics use cases.
• Demonstrate ability to apply software engineering best practices including version control code reviews testing strategies and continuous integration for data projects.
• Exhibit strong problem solving skills attention to detail and a focus on building data solutions that meaningfully improve healthcare affordability access and outcomes.