Daniel Pogrebinsky

Bachelor's

Computer Science

John Deere

Software Engineer Intern

• Developed proof of concept for data streaming pipeline (ETL) to process 25TB monthly. Successfully delivered end-to-end implementation using AWS, Apache Spark, and Databricks Delta Lake. • Led recovery of a critical server outage, housing time-critical data relied upon by ~700 customers. Created emergency pipeline using AWS and Databricks Autoloader to firefight failure within 72 hours. Personally onboarded 20 engineers onto new system, saving >800 engineer hours. • Used Spark UI, Structured Streaming Metrics, and Ganglia to analyze, monitor, and document pipeline metrics: data accuracy and completeness, data processing time, throughput, error and rejection rates, and resource utilization. • Delivered 75 SQL views and bulk data download feature to enable 12 stakeholders to access machine data