Rajesh Veera
About Rajesh Veera
Rajesh Veera is a Lead Data Engineer at Nevro, with extensive experience in cloud platforms and big data technologies. He has held various engineering roles at companies such as BMK Solutions LLC, Wells Fargo, Shutterfly, and General Motors Europe, and holds a Master's degree from HSB Hochschule Bremen.
Work at Nevro
Rajesh Veera has been employed at Nevro as a Lead Data Engineer since 2020. In this role, he is responsible for overseeing data engineering tasks and managing data infrastructure. His work involves utilizing cloud platforms and big data technologies to enhance data processing capabilities within the organization. Nevro, known for its innovative solutions in pain management, benefits from Rajesh's expertise in building modular and reusable ETL/ELT pipelines.
Previous Experience in Data Engineering
Prior to his current position at Nevro, Rajesh Veera worked at Shutterfly, Inc. as a Senior Data Engineer from 2015 to 2020. He also held a position as a Data Engineer at Wells Fargo for 10 months in 2014-2015. His earlier roles include working as an Integration Engineer at BMK Solutions LLC and General Motors Europe in Frankfurt Am Main Area, Germany, from 2008 to 2010. Additionally, he worked as a Software Engineer at Adroitent in Hyderabad, India, from 2011 to 2012.
Education and Expertise
Rajesh Veera holds a Master's degree from HSB Hochschule Bremen – City University of Applied Sciences. He also earned a Bachelor of Technology (BTech) from Jawaharlal Nehru Technological University. His educational background supports his proficiency in various database systems, including Snowflake, Redshift, PostgreSQL, Teradata, and MongoDB. He is experienced in cloud platforms and big data technologies such as AWS, Hadoop, and Apache Spark.
Technical Skills and Technologies
Rajesh possesses extensive technical skills in data engineering. He is proficient in managing data infrastructure and implementing batch and stream processing systems. His expertise includes building modular and reusable ETL/ELT pipelines using distributed databases. He utilizes a wide range of technologies in his work, including Airflow, DBT, Databricks, and Data Lake, to optimize data workflows and enhance data processing efficiency.