Srujan Jabbireddy
About Srujan Jabbireddy
Srujan Jabbireddy is a Data Engineer with a Master's degree in Industrial and Systems Engineering from Texas A&M University. He has over 11 years of experience, currently working at uShip and previously at Oracle, where he developed automated data pipelines and collaborated with business teams to create data solutions.
Work at uShip
Srujan Jabbireddy has been employed at uShip as a Data Engineer since 2021. In this role, he is responsible for developing and maintaining data pipelines that support the company's operations. His work involves implementing automated processes that enhance data management and accessibility, contributing to the overall efficiency of the organization.
Current Role at Oracle
Srujan Jabbireddy has served as an Associate Technical Consultant at Oracle since 2013. His responsibilities include retrieving large datasets using SQL and automating workflows with Python. He has also automated server agent installations and monitored their status within the Oracle Enterprise Manager 12c Cloud IT monitoring tools ecosystem.
Education and Expertise
Srujan Jabbireddy earned a Master's degree in Industrial and Systems Engineering from Texas A&M University, studying from 2019 to 2021. Prior to this, he completed his Bachelor of Engineering in Mechanical Engineering at Osmania University College of Engineering from 2009 to 2013. His educational background provides a strong foundation for his work in data engineering and analytics.
Professional Experience
Before his current roles, Srujan worked as a Student Assistant at Texas A&M University from 2019 to 2020. He also interned at the Texas A&M Institute of Data Science, where he contributed to operational data science projects from 2020 to 2021. His experience includes developing automated data pipelines using AWS, Snowflake, and dbt, as well as designing data models for enterprise data warehouses.
Technical Skills and Projects
Srujan Jabbireddy has developed automated data pipelines and frameworks to monitor data quality and pipeline performance. He has experience in Agile and DevOps processes and has built batch data systems for machine learning price predictions. His technical skills include proficiency in SQL, Python, AWS, and dbt, which he applies to create scalable data solutions that address business challenges.