Summary
Stephen Perl is a Data Engineer with a decade of experience building scalable data platforms and real-time pipelines, currently driving data initiatives at Meta from Houston. He combines a Computer Science degree from UT Austin with hands-on expertise in Python, JavaScript, AWS serverless architectures, Spark/EMR, and MySQL-based modeling to deliver end-to-end solutions—from data lakes and ETL to production REST APIs. His background spans reducing data latency to near real-time using Kinesis/Lambda and leading cross-functional teams to ship high-availability services and observability for complex pipelines. Notably, he has bridged product and engineering needs at both enterprise e-commerce and analytics businesses, and has saved organizations substantial licensing and processing costs through pragmatic system design. Colleagues rely on him to translate ambiguous requirements into auditable, test-driven implementations that scale.
10 years of coding experience
5 years of employment as a software developer
Bachelor's degree, Computer Science, Bachelor's degree, Computer Science at The University of Texas at Austin
English, Japanese