Rohan Somisetty

Innovative Data Engineer with 3+ years of experience in architecting and optimizing high-performance data pipelines and ETL processes. Expertise in cloud platforms (AWS, Azure), big data ecosystems (Apache Spark, Databricks), and data warehousing

(Snowflake, Redshift). Proficient in Python and SQL, with a track record of reducing data processing times by 30% and improving data reliability by 25%. Strong analytical skills and a proactive collaborator with excellent communication abilities.

I am an innovative Data Engineer with over 3 years of experience designing and optimizing high-performance data pipelines and ETL processes. My expertise spans cloud platforms like AWS and Azure, big data ecosystems such as Apache Spark and Databricks, and data warehousing tools like Snowflake and Redshift. I excel in Python and SQL, with a proven track record of improving data processing efficiency by 30% and enhancing data reliability by 25%.

At Goldman Sachs, I engineered scalable pipelines, automated infrastructure provisioning with Terraform, and optimized ETL workflows using Databricks, leading to significant performance improvements. I also deployed Kubernetes on AWS EKS to enhance microservices efficiency and designed BI solutions on Azure, boosting data accessibility and reporting efficiency.

Previously at Coforge, I built and optimized ETL pipelines, collaborated with data scientists to streamline machine learning model deployment, and created impactful data visualizations with Tableau and Power BI. These efforts improved decision-making speed and operational efficiency.

With a strong background in cloud platforms, big data, and data visualization, I bring analytical skills, technical expertise, and a proactive approach to solving complex data challenges.

I hold a Master’s degree in Computer and Information Sciences from the University of Colorado Denver and a Bachelor’s degree in Computer Science from CVR College of Engineering, JNTU. My education provided a strong foundation in computer science principles, data systems, and advanced analytical methods, which I have applied throughout my career as a Data Engineer.