Anirudh Jyothi
About Anirudh Jyothi
Anirudh Jyothi is a Senior Data Engineer at Milliman in the Greater Chicago Area, where he has worked since 2020. He has a diverse background in data engineering and analysis, with previous roles at Aetna, The Allant Group, and the UIC Business Career Center.
Work at Milliman
Anirudh Jyothi has been employed at Milliman as a Senior Data Engineer since 2020. In this role, he has conducted webinars and training sessions to promote the use of Databricks, successfully reaching over 100 users from various disciplines. He has also co-led a project that transitioned on-premise data workflows to the Cloud using Databricks, which resulted in significant annual savings of approximately $500,000 in hardware and software licensing costs. His work involves implementing data pipelines utilizing technologies such as Python, PySpark, Spark SQL, AWS S3, and EC2, achieving over a 95% reduction in processing and querying times.
Education and Expertise
Anirudh Jyothi holds a Bachelor of Engineering (B.E.) in Geo-Informatics from Anna University. He furthered his education by obtaining a Master's degree in Computer Information Systems with a focus on Data Science from the University of Illinois Chicago. His educational background provides a strong foundation for his expertise in data engineering and analytics.
Background
Anirudh Jyothi has a diverse professional background in data analysis and engineering. He began his career as a Research Intern at the Indian Institute of Remote Sensing, ISRO, in 2008. He then worked as a Programmer Analyst at Aetna from 2010 to 2012. Following this, he served as a Teaching Assistant and Graduate Assistant at the UIC Business Career Center from 2012 to 2014. He also worked as a Data Analyst at The Allant Group from 2014 to 2016 and as a Technical Analyst Intern at the Chicago Health Information Technology Regional Extension Center in 2013.
Achievements
Throughout his career, Anirudh Jyothi has achieved notable milestones in data engineering. He has successfully implemented data pipelines that have significantly reduced processing and querying times by over 95%. His leadership in migrating data workflows to the Cloud has resulted in substantial cost savings for his organization. Additionally, he has actively contributed to the professional development of others through training sessions on Databricks.