Nikhil Rastogi

• Collaborated with cross-functional teams in an Agile environment to translate business requirements into scalable data solutions, aligning claims processing and eligibility validation workflows with analytics objectives and improving delivery efficiency by 20%. • Developed and enforced scalable batch and streaming data pipelines on AWS to process 1.8M+ healthcare claims and eligibility records monthly, reducing processing latency by 25%. • Automated end-to-end workflow orchestration using AWS Step Functions, reducing manual intervention by 70% and accelerating data delivery timelines by 30% through streamlined pipeline execution and monitoring. • Developed modular, event-driven AWS Lambda functions to handle data transformations and system integrations, reducing operational overhead by 45% and improving platform scalability. • Engineered Change Data Capture (CDC) pipelines for Amazon Redshift and Hive to enable incremental data loads, ensuring 99.8% real-time data consistency across high-volume claims datasets. • Led migration of a large-scale data lake to an optimized Amazon Redshift data warehouse using AWS EMR, restructuring schemas and tuning queries to reduce analytics query runtime by 60%. • Designed and implemented a comprehensive data quality framework incorporating cleansing, validation rules, and anomaly detection, improving dataset accuracy by 25% and enhancing reliability of claims and eligibility reporting. • Automated data validation and transformation workflows using Python, Scala and Pyspark, embedding business rules for claims adjudication and eligibility checks, reducing manual data corrections by 35% and improving overall data integrity.

• Database Management & Optimization: Optimized Azure SQL and MySQL clusters for high availability and horizontal scaling, significantly improving query performance and system throughput. • Data Architecture & ETL: Engineered Azure Data Factory pipelines and Blob Storage solutions to streamline data integration and manage both structured and unstructured data storage.