keerthi chakravarthula

I’m an analytics-focused data engineer with hands-on experience building cloud-based pipelines, dashboards, and automated reporting that help teams make better decisions. I translate high-volume data into measurable KPIs, validate integrations, and improve reliability through disciplined data quality practices.

At Amazon, I designed and built scalable data pipelines with PySpark and Databricks to process API logs and transactions. I developed interactive Power BI dashboards to track API volumes, user behavior, and system performance, and I also created automated Excel reporting (pivot tables and macros) that reduced manual effort by 40%.

Beyond dashboards, I worked deeply in data processing and performance monitoring—processing and transforming datasets with Python (Pandas) and PySpark, ingesting data from AWS S3 and Databricks, and using AWS CloudWatch to connect system metrics to actionable insights. I performed root cause and trend analysis on API failures and support tickets, improving how teams understand recurring issues by backing recommendations with data.

Most recently, as an Information Technology Intern at FedEx in the Global Timekeeping organization, I analyzed workforce scheduling and timekeeping data to support enhancements to ERMA and workforce optimization initiatives. I validate data integrations across UKG Workforce Management, ERMA, and internal systems using SQL, REST APIs, Java, and Spring Boot, and I contributed to deployment verification using Agile/Scrum practices. I also bring a practical, model-driven mindset through projects in forecasting, computer vision, and real-time detection systems, and I was awarded Best Performer at Amazon for analytics and automation contributions.