This track focuses on classic and modern data engineering workflows, databases and more. Some talks also discuss pipelines and systems that are tailored to data science and machine learning tasks.
Our speakers will cover high-level architectures, best practices and detailed solutions for designing large scale pipelines and databases, reproducibility of ML experiments, automated deployment of ML models in production, algorithms for optimization of a new generation of databases and continuous data pipeline monitoring.
This track will appeal to hands-on data engineering practitioners who fluidly cross the boundary between development and operations.
Wes is Director of Engineering, Advanced Analytics at Cortico. He's also Technical Advisor at Chartbeat and a Visiting Researcher at the Laboratory for Social Machines at the MIT Media Lab.
Masha Danilenko is currently getting her new project off the ground: LadyEng.com, a free online education targeting early career professional women. Previously she was leading a 100% women team at Insight Data Science as an Engineering Lead. As part of that role, she has helped over a hundred professionals transition into Data and DevOps Engineering roles across North America.
A pure mathematician by training with a Master's from Moscow State University, she transitioned from academia to industry and worked as a System Analyst Lead prior to moving to the US. After the move, she became a Data Engineering Fellow at Insight and then joined Capital One Labs as a Data Engineer.