Rishita Rao
About Rishita Rao
Rishita Rao is a Data Engineer at Lotlinx, Inc., where she has worked since 2023. She has a strong background in data engineering and machine learning, with previous roles at Omdena, Levio, and Deloitte India.
Work at Lotlinx
Rishita Rao has been employed at Lotlinx, Inc. as a Data Engineer since 2023. In this role, she has developed a Change Data Capture (CDC) based event-driven architecture to improve data processing efficiency. Additionally, she has implemented data pipelines that integrate with multiple APIs, optimizing vehicle inventory management. Her contributions focus on enhancing data workflows and streamlining operations within the organization.
Previous Experience in Data Engineering
Before joining Lotlinx, Rishita Rao worked at Levio as a Data Engineer from 2021 to 2023. Prior to that, she served as a Junior ML Engineer at Omdena for six months in 2020. Her experience in these roles provided her with a solid foundation in data engineering and machine learning, allowing her to develop skills essential for her current position.
Educational Background
Rishita Rao holds a Master's degree in Big Data from Trent University, which she completed from 2019 to 2021. She also studied at the Indian School of Business, where she achieved a Technology Entrepreneurship Program from 2015 to 2017. Earlier, she earned a Bachelor's degree in Electrical, Electronics and Communications Engineering from Osmania University, Hyderabad, from 2013 to 2017.
Contributions to Social Impact Initiatives
Rishita Rao participated in the Omdena AI challenge in collaboration with the World Resource Institute. This involvement highlights her commitment to leveraging data engineering skills for social impact, demonstrating her ability to apply technical knowledge in real-world scenarios aimed at addressing societal challenges.
Technical Skills and Achievements
Rishita Rao has designed and built Slowly Changing Dimension (SCD) type 2 Sqlmesh models, which have automated data backfilling and version control. This initiative has significantly reduced manual data management efforts by 20 hours per week. Her technical expertise is evident in her ability to handle complex data integrations and optimize data processing workflows.