Data Standard Audio Experience with Netflix’s Bhargavi Reddy Dokuru

The Data Standard

Data Standard Audio Experience with Netflix’s Bhargavi Reddy Dokuru
Netflix’s Bhargavi Reddy Dokuru, joins The Data Standard to talk about Data Engineering in the Workplace.

Episode Summary

There’s no denying how critical data is for businesses across industries and niches. Companies rely on data for everything from marketing to customer conversions. However, to make use of the available data, it’s essential to have the proper tech architecture that can support data collection and analysis.
Catherine Tao and Bhargavi Reddy Dokuru have sat down in today’s podcast to discuss the importance of data engineering in the workplace. Bhargavi has years of experience building scalable data infrastructures that drive results. She shares her unique insights on what it takes to establish an efficient data pipeline that improves data utilization and effectiveness.
Scalability of the tech architecture, recoverability of data, and query performance are three of the most important aspects of proper data engineering in any company. Have a listen to the podcast to learn more about what data engineering in the workplace involves and why it’s so important.

Meet the Hosts

Catherine Tao

Data scientist at The Data Standard
Catherine Tao is a tech enthusiast looking for new methods for building connections with businesses around the world. Her extensive knowledge of data science allowed her to develop new solutions and implement them into existing ecosystems. She is currently working as a Data scientist and Exclusive Podcast Producer at The Data Standard.

Bhargavi Reddy Dokuru

Senior Data Engineer at Netflix
Bhargavi is an experienced Big Data professional who’s spent years in the industry perfecting her skills. She has an MA in Information Systems Management and has an extensive professional background, working as a Business Intelligence Engineer at Amazon before joining Netflix as a Data Engineer. She’s focused on enhancing data-driven decision making and building scalable data infrastructures.