Harsha M

About Harsha M

With over 9 years in IT and over 5 years specializing as a Big Data/Hadoop Developer, I…

Experience

1. Sr Gcp Data Engineer

   Mutual of Omaha

   Feb 2022 — Present · NE, US

   Designed and implemented scalable and secure storage solutions using cloud storage services. Configured lifecycle policies to manage data retention and reduce storage costs. Automated data backup processes to protect against data loss and ensure disaster recovery. Integrated cloud storage solutions with data processing workflows to enable seamless data handling. Developed and maintained Python scripts for data extraction, transformation, and loading ETL processes. Implemented machine learning models using Python libraries such as scikit-learn, TensorFlow, and Keras. Optimized existing Python code for better performance and scalability. Monitored and optimized cloud storage performance to maintain efficiency and cost-effectiveness. Designed and optimized data flow architectures to facilitate efficient data movement and processing. Developed data flow diagrams to map out the movement and transformation of data across systems. Integrated various data sources and sinks to create unified data processing pipelines. Configured data flow tools and platforms to manage and orchestrate data pipelines. Documented data flow processes and maintained records for auditing and troubleshooting purposes. Trained and evaluated machine learning models using various algorithms and techniques. Integrated machine learning models into production systems for real-time predictions and decision-making. Collaborated with data scientists and engineers to refine and optimize machine learning workflows. Developed and maintained robust data pipelines to automate the extraction, transformation, and loading (ETL) of data. Implemented data pipeline frameworks to handle large volumes of data and ensure reliability. Optimized data pipeline performance to reduce latency and improve data processing speed. Documented data pipeline configurations and processes to facilitate maintenance and updates. Conducted performance tuning and troubleshooting to ensure efficient data pipeline operations.