jayasree Hasti

I've built large-scale data pipelines across projects for Licious, Malcom, Kellogs, and Samsung, processing structured and semi-structured data with Spark, Hadoop, Hive, and cloud platforms.

At Licious, I develop PySpark transformations on AWS EMR and S3, integrate Airflow with AWS services for event-driven workflows, and optimize Spark Streaming for low-latency processing. I also work with Azure services including Data Lake, Blob Storage, Azure Functions, Azure Monitor, and Application Insights.

For Malcom and Kellogs, I designed and optimized ETL workflows using PySpark, Spark SQL, Airflow, Sqoop, HDFS, and Hive. My work includes partitioning, caching, broadcast joins, query tuning, schema evolution, and reliable ingestion pipelines.

I've supported end-to-end Hadoop data solutions from requirements analysis through testing and troubleshooting. I focus on data quality, performance, scalability, and dependable production pipeline execution.