Ashitha Raj Uppalapati
Big Data Engineer @SABIC
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WORK HISTORY
Big Data Engineer @SABIC
US
Architect and deliver production-grade data platforms supporting real-time analytics, enterprise search, and business intelligence at scale. Lead engineering decisions, enforce data governance, and mentor the team. Designed end-to-end Medallion (Bronze/Silver/Gold) pipelines on Azure Databricks with Delta Lake, cutting data latency from hours to minutes for downstream BI and search consumers. Built Kafka-based streaming ingestion processing millions of events/day; engineered NiFi and Spark batch workflows across 50+ source schemas with schema evolution and data contract enforcement. Reduced pipeline failures 35% through automated monitoring, root-cause analysis, and CI/CD pipeline implementation — eliminating repeat incidents. Implemented Unity Catalog governance: column-level masking, fine-grained RBAC, and audit logging aligned to SOC 2 data access standards. Mentored 2 junior engineers on Spark optimization and Kafka streaming patterns; led design reviews enforcing data quality and regulatory compliance across all pipelines.Stack: Apache Spark · PySpark · Kafka · Azure Databricks · Delta Lake · NiFi · Unity Catalog · Hadoop · Python · CI/CD · Git
EDUCATION
Arizona State University
Master's degree, Information Technology
GITAM Deemed University
Bachelor's degree, Computer Science
ABOUT ASHITHA RAJ UPPALAPATI
As a Big Data Engineer at SABIC, I architect and deliver robust data platforms tailored for real-time analytics, enterprise search, and business intelligence. My work includes designing Medallion pipelines on Azure Databricks, implementing Kafka-based streaming ingestion, and ensuring data governance through CI/CD practices. I hold a Master’s degree in Information Technology from Arizona State University and a Bachelor’s in Computer Science from GITAM Deemed University. My expertise lies in Lakehouse architectures, Delta Lake, and tools like Spark, NiFi, and Kafka, which I employ to drive seamless data transformation and timely analytics for businesses.
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