Nimbus Goehausen
About Nimbus Goehausen
Nimbus Goehausen is a Staff Data Engineer at Prophecy in San Francisco, California, with a strong background in big data and data science. He has held various engineering roles at notable companies, including Instagram, Bloomberg LP, and Salesforce, and emphasizes trust, honesty, and learning within software teams.
Work at Prophecy
Nimbus Goehausen has served as a Staff Data Engineer at Prophecy since 2021. In this role, he focuses on big data and data science, applying his expertise to develop effective data solutions. His work emphasizes selecting the appropriate tools for specific tasks, which enhances the efficiency and effectiveness of data operations within the organization.
Previous Experience in Data Engineering
Prior to joining Prophecy, Nimbus Goehausen held various positions in data engineering. He worked at Instagram as a Data Engineer for 11 months in 2019, contributing to data-driven projects. He also served as Principal Data Engineer at Demandbase from 2017 to 2019, where he played a key role in data management and strategy. His experience includes a brief tenure as Lead Data Engineer at Salesforce in 2017.
Background in Software Engineering
Nimbus Goehausen has a solid background in software engineering, having worked at Bloomberg LP as a Senior Software Engineer from 2015 to 2017. He also gained experience at Radius Intelligence, Inc. as Lead Data Scientist from 2010 to 2015. His early career included roles at UC Berkeley, where he worked as an Engineer and SLC Tutor, providing him with a diverse skill set in both engineering and education.
Education and Expertise
Nimbus Goehausen studied at the University of California, Berkeley, where he earned a Bachelor of Arts degree in Physics and Computer Science from 2004 to 2009. His educational background laid the foundation for his expertise in big data and data science, allowing him to approach software engineering with a focus on simplicity and robustness.
Professional Philosophy
Nimbus Goehausen advocates for a culture of experimentation within software teams, viewing failure as a learning opportunity. He emphasizes the importance of trust, honesty, and continuous learning in team dynamics. His pragmatic approach to software engineering involves building simple, easily replaceable solutions, which reflects his commitment to effective and sustainable software development.