Summary
Lokesh Mamidi is a data engineering specialist with 14 years of software experience and 4+ years focused on building analytics-ready pipelines, data models, and reporting platforms across financial and automotive domains. He designs scalable batch ETL frameworks using Python, SQL, PySpark, and orchestration tools (Control‑M/Airflow), and has delivered warehouse-style staging/final models and SLA-driven workflows that cut manual reconciliation effort by around 90%. His work spans high-throughput sensor data architectures at multi‑terabyte scale and enterprise cashflow forecasting for Freddie Mac, blending data engineering rigor with analytics-facing outputs and reconciliation reporting. Comfortable across backend services (FastAPI), cloud databases (Amazon Aurora), and visualization, he also brings teaching and mentorship experience from George Mason University, indicating strong communication and technical coaching skills. Not obvious from titles alone: he pairs hands‑on pipeline optimization with practical ML exposure (ensemble models, time-series forecasting) and a penchant for turning messy multi-source data into trusted datasets for decision-making.
14 years of coding experience
4 years of employment as a software developer
Bachelor's degree, Computer Science, Bachelor's degree, Computer Science at NIIT University
Master of Computer Science, Computer Science, Master of Computer Science, Computer Science at George Mason University
English, Telugu, Hindi