Sai Reddy C
Data Engineer @UnitedHealth Group
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WORK HISTORY
Data Engineer @UnitedHealth Group
Architect and maintain scalable ETL/ELT pipelines processing 10M+ healthcare records using AWS (S3, Glue, Athena) and Snowflake to support enterprise analytics and regulatory reporting. • Develop and manage serverless ETL jobs using AWS Glue to transform structured and semi-structured data stored in S3 for downstream Snowflake ingestion. • Utilize AWS Athena for large-scale ad-hoc querying and data validation, accelerating troubleshooting and improving data verification efficiency. • Design and optimize complex SQL transformations (CTEs, window functions, performance-tuned joins) to support claims, provider, and member analytics. • Implement incremental data loading frameworks and automated data quality checks, maintaining 99%+ accuracy across critical healthcare datasets. • Orchestrate end-to-end workflows using Apache Airflow, Azure Data Factory (ADF), and Alteryx, reducing manual intervention by 40% and improving pipeline reliability. • Build and optimize star-schema dimensional data models to enhance query performance and enable scalable BI and reporting solutions. • Ensure HIPAA-compliant handling of PHI through encryption, RBAC, secure storage practices, and continuous performance tuning to improve SLA adherence and cost efficiency.
EDUCATION
Sri Venkateswara College of Engineering and Technology, Chittoor
Bachelor of Engineering - BE, Computer Science
Trine University
Master’s, Information Science/Studies
ABOUT SAI REDDY C
Data Engineer with 5+ years of experience building scalable, high-performance cloud data platforms that power enterprise analytics and mission-critical decision-making.At UnitedHealth Group, I design and optimize ETL/ELT pipelines processing 10M+ healthcare records using AWS (S3, Glue, Athena), Snowflake, Airflow, and Azure Data Factory. I specialize in transforming complex, high-volume data into reliable, analytics-ready datasets through strong SQL engineering, dimensional modeling (star schema), incremental frameworks, and automated data quality controls.I thrive in fast-paced environments where ownership, performance optimization, and scalability matter. My work has improved pipeline reliability, reduced manual intervention, and ensured 99%+ data accuracy while maintaining strict HIPAA compliance standards.Core strengths:• Cloud Data Engineering (AWS & Azure)• Advanced SQL & Performance Tuning• Python-Based Data Processing• Data Modeling & Warehousing• Workflow Orchestration & Automation• Data Governance & Quality FrameworksI’m passionate about building modern, scalable data ecosystems that reduce manual work, increase visibility, and enable smarter business decisions.Open to opportunities in Senior Data Engineering, Cloud Data Engineering, and Data Platform roles where I can drive both hands-on delivery and architectural impact.
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