Harsha Dandu
About Harsha Dandu
Harsha Dandu is a Lead Data Engineer with a Bachelor's Degree in Production Engineering from the National Institute of Technology Surat. He has extensive experience in data analytics and engineering, having worked with notable companies such as Uber, Capital One, and Opsera.
Work at Opsera
Harsha Dandu currently serves as the Lead Data Engineer at Opsera, a position he has held since 2022. In this role, he has been instrumental in designing the architecture for data products and creating a roadmap for analytics initiatives. As the first member of the data and analytics team, he has built a team of three engineers, showcasing his leadership and team-building skills. His work includes engineering an end-to-end data stack, demonstrating his expertise in data architecture and engineering.
Education and Expertise
Harsha Dandu earned his Bachelor’s Degree in Production Engineering from the National Institute of Technology Surat, completing his studies from 2008 to 2012. His educational background provides a strong foundation in engineering principles, which he applies in his data engineering roles. His expertise includes data architecture, data transformation, and analytics, with a focus on optimizing data handling processes.
Professional Background
Harsha Dandu has a diverse professional background in data engineering and analytics. He began his career at Tata Consultancy Services as a Database Engineer from 2012 to 2014. He then worked at Redmart India Private Limited as a BI/Data Engineer for nine months in 2015, followed by a two-year tenure as a Data Analyst at Capital One from 2016 to 2018. He further advanced his career at Uber as a Senior Data Analyst from 2018 to 2021, before taking on the role of Lead Data Analytics at CarDekho for one year in 2021.
Key Achievements
Throughout his career, Harsha Dandu has achieved significant milestones in data engineering. He reduced infrastructure costs by performing ELT within ClickHouse, avoiding the use of microservices for raw data transformation. He successfully converted MongoDB KPI queries to ClickHouse dialect SQL, achieving a query duration of less than 100 milliseconds. Additionally, he migrated log data from the ELK stack to ClickHouse, creating a timeseries of log data that provided an alternative to in-house monitoring solutions.