Chandrashekar Goud

Background

About Chandrashekar Goud

With 7+ years of experience in designing, building, and deploying scalable data solutions, I specialize in cloud-native architectures, big data processing, and ETL optimization. My expertise lies in transforming raw data into actionable insights, enabling businesses to make data-driven decisions efficiently. I have designed and deployed containerized data applications using Docker and Kubernetes, ensuring high availability and efficient resource utilization. Managing data lakes on AWS S3, I optimize storage for large-scale analytics while leveraging Databricks Delta Lake for reliable and scalable warehousing. I build high-performance ETL pipelines using Apache Airflow, Databricks (PySpark), and DataStage, processing terabytes of data to drive advanced analytics. My experience with CI/CD pipelines (GitHub Actions) streamlines deployments, ensuring rapid and reliable data delivery. Additionally, I optimize Oracle SQL queries, troubleshoot legacy ETL processes, and automate workflows using shell scripting. Passionate about data engineering, cloud technologies, and automation, I always seek innovative ways to enhance data ecosystems and drive business success.