Summary
Jingliang Zhang is a Senior Big Data Software Engineer with nine years’ experience building production ML and data platforms across Azure, AWS and hybrid cloud environments. He designs and optimizes deep learning OCR pipelines, scalable ETL/analytics workflows (Spark, Databricks, Kafka) and secure cross-cloud networking solutions that reduce cost and improve throughput. At AT&T he modernized OCR with AKS autoscaling, Linkerd pod-to-pod encryption and async processing while also enabling automated model/data sync between Azure and AWS. His background in mechanical engineering and applied research gives him a strong foundation in simulation, diagnostics and signal processing—skills he has applied to industrial prognostics, EDI parsing and telecom cost-savings analytics. Comfortable bridging data science and engineering, he also builds developer tooling and automation (Airflow, Jenkins, Python libraries) to make complex pipelines reliable and auditable. Based in Alpharetta, GA, he combines research rigor with hands-on cloud-native execution to drive measurable business impact.
9 years of coding experience
13 years of employment as a software developer
MS, Mechanical Engineering, MS, Mechanical Engineering at University of Cincinnati
Master's degree, Computer Science/Machine Learning, Master's degree, Computer Science/Machine Learning at Georgia Institute of Technology
Mechanical Engineering, Mechanical Engineering at University of Delaware
Bachelor's degree, Automotive Engineering, Bachelor's degree, Automotive Engineering at Beijing Institute of Technology
English, Japanese, Chinese