Sr. Developer

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"AIA - Coimbatore" Weekend Drive - 31-Oct-2026

Interview Mode - Face to Face

Exp Range - 6 - 8 Years

Location: Coimbatore

Skill: GCP, BigQuery and Python -

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 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 efficient 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 services quickly and prevent recurrence.
  • Create and maintain technical documentation for data flows pipeline configurations and data models to support transparency audit readiness and knowledge sharing.
  • Partner with data security and compliance teams to embed privacy access controls and governance practices into all payer data solutions.
  • Contribute to continuous improvement by evaluating new cloud features proposing performance enhancements and refining existing data engineering patterns.
  • Mentor peers on best practices in cloud based data engineering to uplift team capability and improve delivery quality for payer clients.


Qualifications

  • Demonstrate strong hands on experience in designing and developing data pipelines with Cloud Composer and Cloud Dataproc in production grade environments.
  • Exhibit advanced proficiency in PySpark and Python for building scalable data processing jobs including tuning and optimization for large healthcare datasets.
  • Show proven expertise in BigQuery and Cloud SQL for data modeling query optimization and secure data access suitable for payer analytics scenarios.
  • Bring solid understanding of payer domain concepts such as claims eligibility members and providers to design context aware data solutions.
  • Display experience working within a hybrid work model and collaborating with distributed teams using agile methods and modern development practices.
  • Apply knowledge of data quality testing strategies and version control to deliver reliable well validated and maintainable code for long term use.
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