prasanth nakka

I am a Data Engineer with five years of experience building and automating data pipelines, cloud infrastructure, and analytics systems across AWS, Azure, and GCP. I focus on scalable ETL workflows, real-time streaming, and data lake/warehouse architectures.

I design reusable Python ETL frameworks using Pandas and PySpark, and I have accelerated data processing and validation across teams by 45%. I architect data lakehouse solutions, implement partitioning and compression strategies, and optimize BigQuery and Redshift for analytics performance and cost.

On the DevOps side, I automate cloud provisioning and CI/CD with Terraform, Ansible, Docker, Kubernetes, Jenkins, and GitHub Actions, reducing setup time by 60% and enabling reliable deployments. I build monitoring and observability with Prometheus, Grafana, CloudWatch, and implement data validation with Great Expectations.

I collaborate closely with analytics and ML teams to deliver curated feature datasets and ML-integrated ETL, supporting model training and productionization. I prioritize data quality, automation, and cross-team enablement to deliver resilient, insight-driven platforms.