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Chandana Sorakundla
Senior Data Engineer @Liberty Mutual Insurance
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WORK HISTORY
Senior Data Engineer @Liberty Mutual Insurance
Owned and built enterprise-scale data pipelines across insurance domains including policy, claims, billing, underwriting, and customer analytics. Developed and optimized batch and near–real-time pipelines using Apache Spark (PySpark), Hive, and Hadoop for high-volume insurance data. Built PySpark-based ingestion frameworks to automate data movement from legacy systems and Oracle into cloud data lakes and Snowflake. Optimized Hive tables using partitioning and bucketing strategies, improving query performance for large claims and policy datasets. Automated ingestion and transformation of 25+ GB daily, delivering curated datasets for analytics and reporting. Implemented orchestration using Spark pipelines and Snowflake Tasks, ensuring reliable scheduling and downstream consumption. Utilized AWS S3 and Amazon Athena for scalable storage and ad-hoc analytics on claims and customer data. Implemented data quality, validation, and reconciliation frameworks using Python and SQL, improving data accuracy by 15%+. Enabled AI/ML use cases by delivering feature-ready datasets for fraud detection, forecasting, and customer churn analysis.
EDUCATION
University of North Texas
Master of Science - MS, Data Science
KL University
Bachelor of Technology - BTech, Electrical and Electronics Engineering
ABOUT CHANDANA SORAKUNDLA
As a highly motivated Data Engineer and Data Science graduate student at the University of North Texas, with 4+ years of hands-on experience building large-scale data platforms across insurance, digital commerce, and product analytics domains, I am passionate about transforming complex data into reliable insights. Currently pursuing my Master’s degree in Information Science (Data Science track), I continue to deepen my expertise in data engineering, analytics, and AI/ML enablement. I have strong experience designing batch and streaming pipelines, working with Spark, Snowflake, Kafka, and cloud platforms such as AWS and Azure. I am eager to contribute my technical and analytical skills to high-impact teams, helping organizations make data-driven decisions at scale.Earlier in my career, I helped scale data systems at a fast-growing product startup, building Kafka-based pipelines, automated data quality checks, analytics models, and dashboards that directly improved user engagement, revenue growth, and operational efficiency.What I bring:Strong ownership of end-to-end data pipelinesDeep expertise in Spark, Snowflake, Kafka, SQLCloud-native design on AWS & AzureFocus on data quality, performance, and governanceAbility to bridge engineering and business needsComfortable working in Agile, production-critical environmentsI’m passionate about building data platforms that are scalable, trustworthy, and ready for advanced analytics and machine learning, and I enjoy collaborating with engineers, analysts, and stakeholders to solve complex data problems.
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