About

Matthew Itomlenskis is a Senior Software Engineer at Google with over 9 years of experience in software development. He is currently working as a Software Engineering Manager in KPMG's Data & Analytics group, where he specializes in cutting-edge technologies and has gained business acumen in various domains. Matthew has worked in the fields of medical imaging, finance, and real-time big data analytics, and is currently interested in using big data technologies along with machine learning to gain insight and solve real-world problems. At KPMG, Matthew is the technical lead to KPMG's Signals Repository, an in-house analytics platform used to collect, analyze, and constantly update +5TB of publicly available data. He has rearchitected the platform to gain 10x improvement in performance at half the cloud consumption cost by utilizing services such as AWS RDS, AWS Redshift, AWS S3, and AWS EMR. He has also migrated the backend REST API framework from Ruby on Rails to Django and scaled the platform globally to include KPMG member firms from +15 countries and external clients. Matthew has built a custom scoring engine in Python and R that uses ML to provide scores, recommendations, and alerts. He is also part of the platform governance council in charge of strategy and product road map and has managed onshore and offshore software engineers for delivery of technical work streams. Matthew has contributed to various other KPMG projects, including designing and implementing a novel document ETL system on Google Cloud Platform using Python and Hadoop for massive parallel processing, assisting in building a PySpark implementation of the Financial Accounting Standards Boards (FASB) issued Current Expected Credit Losses (CECL) standard used in the banking industry, providing technical architecture recommendations for multiple client engagements, and architecting and building a POC for a firm-wide data lake that combines client data, 3rd party data, and public data for various business groups to consume. Matthew holds a Master of Science (MS) in Computer Science from Georgia Institute of Technology, a Master of Science (MS) in Physics from Cleveland State University, and a Bachelor of Science (BS) in Computer Science and a Bachelor of Arts (BA) in Physics, also from Cleveland State University. His tech stack includes AWS, Senior Software Engineer, Software Engineer, Big Data, ML, Python, Ruby, Hadoop, Elastic Search, ETL, Backend, and Django.