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Data Engineer with 4+ years of experience building, migrating, and operating HIPAA-compliant AWS data platforms supporting clinical, claims, and operational analytics. Proven track record designing scalable batch and near real-time pipelines using Python, Spark, Airflow, AWS Glue, and Redshift, improving data reliability, audibility, and analytics readiness across healthcare domains. Experienced in modernizing legacy Hadoop environments to cloud-native architectures, implementing data quality and governance controls for PHI, and partnering with analytics, product, and compliance teams to deliver secure, production-grade data solutions.…Data Engineer with 4+ years of experience building, migrating, and operating HIPAA-compliant AWS data platforms supporting clinical, claims, and operational analytics. Proven track record designing scalable batch and near real-time pipelines using Python, Spark, Airflow, AWS Glue, and Redshift, improving data reliability, audibility, and analytics readiness across healthcare domains. Experienced in modernizing legacy Hadoop environments to cloud-native architectures, implementing data quality and governance controls for PHI, and partnering with analytics, product, and compliance teams to deliver secure, production-grade data solutions.

Kamireddy Rajesh Kumar

Data Analyst, Data Scientist, Full Stack Developer, +2

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Data Engineer with 4+ years of experience building, migrating, and operating HIPAA-compliant AWS data platforms supporting clinical, claims, and operational analytics. Proven track record designing scalable batch and near real-time pipelines using Python, Spark, Airflow, AWS Glue, and Redshift, improving data reliability, audibility, and analytics readiness across healthcare domains. Experienced in modernizing legacy Hadoop environments to cloud-native architectures, implementing data quality and governance controls for PHI, and partnering with analytics, product, and compliance teams to deliver secure, production-grade data solutions.…Data Engineer with 4+ years of experience building, migrating, and operating HIPAA-compliant AWS data platforms supporting clinical, claims, and operational analytics. Proven track record designing scalable batch and near real-time pipelines using Python, Spark, Airflow, AWS Glue, and Redshift, improving data reliability, audibility, and analytics readiness across healthcare domains. Experienced in modernizing legacy Hadoop environments to cloud-native architectures, implementing data quality and governance controls for PHI, and partnering with analytics, product, and compliance teams to deliver secure, production-grade data solutions.

Available to hire

Data Engineer with 4+ years of experience building, migrating, and operating HIPAA-compliant AWS data platforms supporting clinical, claims, and operational analytics. Proven track record designing scalable batch and near real-time pipelines using Python, Spark, Airflow, AWS Glue, and Redshift, improving data reliability, audibility, and analytics readiness across healthcare domains.

Experienced in modernizing legacy Hadoop environments to cloud-native architectures, implementing data quality and governance controls for PHI, and partnering with analytics, product, and compliance teams to deliver secure, production-grade data solutions.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Language

English

Fluent

Work Experience

Data Engineer at CVS Health

February 1, 2025 - Present

Improved clinical and patient data reliability by approximately 40% by designing and operating HIPAA-compliant ETL pipelines using Python, Apache Airflow, and AWS Glue, supporting analytics, reporting, and downstream ML use cases. Architected and maintained AWS-based data lakes and warehouses (S3, Redshift) to centralize PHI and operational datasets, enabling compliant self-service analytics and executive dashboards in Tableau and Power BI. Reduced data latency and pipeline failure rates by implementing end-to-end data validation, monitoring, and alerting frameworks using CloudWatch and custom Python checks. Designed and optimized dimensional data models (star and snowflake schemas) in Redshift and PostgreSQL, improving query performance by 50–60% and accelerating healthcare reporting turnaround times. Led migration of legacy Hadoop workloads to Spark on AWS, improving scalability, maintainability, and cost efficiency while aligning with enterprise healthcare data governance standard

Data Engineer at CueTech Systems

January 1, 2020 - July 1, 2023

Designed and implemented cloud-based data lakes and warehouses on AWS (S3, Redshift), automating ingestion workflows and reducing manual data handling by 50%. Built scalable ETL/ELT pipelines using Python, Spark, AWS Glue, and Airflow, enabling near-real-time analytics and improving overall data freshness by 40%. Implemented data quality, validation, and monitoring frameworks using Python, SQL, AWS Lambda, and CloudWatch, significantly reducing production issues and increasing confidence in analytical outputs. Developed hybrid batch and streaming pipelines using Kafka and Spark, modernizing legacy data processing jobs and improving processing throughput by 45%. Supported analytics and ML teams by optimizing feature engineering pipelines and improving secure data accessibility through warehouse modernization initiatives. Automated routine pipeline operations, deployments, and database maintenance using Python, SQL, Docker, and CI/CD pipelines, reducing operational overhead and deploymen