Raghava Nalla

I am a results-driven Data Engineer with over 3 years of experience in building scalable, cloud-based pipelines and data models. My expertise lies in utilizing technologies such as AWS, SparkSQL, Snowflake, and Kafka to create efficient data lake architectures. I have a proven track record of reducing latency and improving reliability in high-volume environments, which has significantly optimized data infrastructure.

At Apple, I designed scalable ETL pipelines that reduced latency by 30% and built data lake solutions that integrated seamlessly with Redshift and Snowflake for high-volume analytics. My role involved creating REST APIs and implementing automated data quality checks, ensuring data integrity across systems. I actively participated in release meetings and collaborated with teams to optimize resource usage and cloud costs.

Previously, at Unum, I built ETL workflows and migrated legacy systems to cloud-based solutions, enhancing reporting accessibility for multiple business units. My experience in predictive modeling and data governance has equipped me to lead stakeholder discussions and convert reporting needs into actionable data products. I am passionate about leveraging data to drive business insights and support decision-making.