Dorothy K.
About Dorothy K.
Dorothy K. is a Data Tech Lead at Handl Health, with a strong academic background in Applied Mathematics, Systems Design Engineering, and Electrical & Computer Engineering from the University of Waterloo. She has extensive experience in data engineering and chip design, having worked at notable companies such as IBM, Ibotta, and Databricks.
Current Role at Handl Health
Dorothy K. serves as the Data Tech Lead at Handl Health, a position she has held since 2024. In this role, she applies her extensive experience in data engineering and technology to lead projects that enhance data management and analytics within the organization. Her responsibilities include overseeing data architecture and implementing data-driven solutions to support the company's objectives.
Professional Background in Data Engineering
Dorothy K. has a diverse professional background in data engineering and technology. She worked at Ibotta, Inc. as a Senior Data Engineer from 2022 to 2023, and at Nutrien Ag Solutions in the same role from 2020 to 2021. Prior to these positions, she was employed at Databricks as a Data Engineer from 2017 to 2020. Her career also includes significant roles at IBM, where she held various engineering positions, contributing to her expertise in data analysis and system characterization.
Educational Qualifications
Dorothy K. holds multiple degrees from the University of Waterloo. She achieved a Bachelor of Mathematics (BMath) in Applied Mathematics, a Master of Applied Science (MASc) in Systems Design Engineering, and a Doctor of Philosophy (Ph.D.) in Electrical and Computer Engineering. Her educational background provides a strong foundation for her work in data technology and engineering.
Contributions to the Field
Dorothy K. has made notable contributions to the field of data engineering and technology. She authored the 'Partitioning and Clustering' chapter in the 'Handbook of Algorithms for Physical Design Automation', showcasing her expertise in algorithms. Additionally, she has developed large-scale network algorithms for chip design and high-performance computing, reflecting her technical proficiency.
Technical Skills and Proficiencies
Dorothy K. possesses a strong understanding of chip architectures, particularly in memory and caches. She is proficient in various machine learning algorithms, including regression, classification, PCA, neural networks, recommender systems, and graph algorithms. Her programming preferences include JVM languages such as Scala, Java, and Kotlin, which align with her solid foundation in programming languages and theoretical concepts.