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.
