Goutham Kakani - Software Engineer - Freddie Mac

Summary

Data Science graduate and Site Reliability Engineer with experience supporting large-scale FinTech production systems through data-driven monitoring, technical troubleshooting, operational support, and software engineering practices. Skilled in Python, Java, SQL/MySQL, system analytics, and cloud-based infrastructure with hands-on experience analyzing high-volume operational data and collaborating with cross-functional engineering teams to improve reliability and customer-impacting systems. Experienced in incident management, workflow optimization, technical documentation, and building scalable monitoring and alerting solutions. Seeking to leverage strong analytical, operational, and software engineering skills in a Product Solutions Engineer role at Google.

Overview

1

Certification

4

years of professional experience

Work History

Software Engineer

Freddie Mac

McLean, VA, USA

07.2022 - Current

Supported large-scale FinTech production systems with greater than 99.9% system availability through proactive monitoring, operational support, and incident management.
Investigated and resolved production incidents by analyzing application logs, telemetry data, metrics, and SQL-based datasets using tools such as Dynatrace, Splunk, and ESS.
Collaborated with software engineering, infrastructure, DevOps, and support teams to troubleshoot customer-impacting technical issues and implement long-term fixes.
Worked on application break fixes, bug resolution, deployment validation, and operational troubleshooting for Java-based backend systems and microservices.
Performed root cause analysis (RCA) for recurring incidents, reducing operational disruptions and improving platform reliability.
Interacted directly with clients and internal stakeholders to manage production escalations, communicate issue status, and ensure timely resolution of high-priority incidents.
Built and enhanced monitoring dashboards and alerting pipelines to improve operational visibility and support faster issue resolution.
Queried and analyzed high-volume operational data using SQL and analytics tools to identify system bottlenecks, performance trends, and failure patterns.
Worked with Java-based microservices and backend systems to support debugging, configuration updates, deployment validation, and issue remediation.
Assisted with CI/CD deployment activities, release validation, operational reviews, and workflow optimization to improve platform stability and release efficiency.
Supported DevOps and cloud-based operational activities involving AWS, Kubernetes, Docker, Jenkins, and CloudWatch.
Automated operational support tasks and monitoring processes using scripting and data-driven analysis techniques.
Partnered with cross-functional teams to improve technical documentation, operational procedures, and troubleshooting workflows.
Applied anomaly detection and predictive monitoring concepts to identify early warning indicators for production failures.
Supported cloud-based infrastructure and containerized environments using AWS, Kubernetes, Docker, and monitoring technologies.

Education

Master of Science - Data Science

University of Maryland Baltimore County

Maryland, USA

06-2022

Bachelor of Technology - Computer Science and Engineering

Koneru Lakshmaiah University

Vijayawada, India

05-2020

Skills

Programming & Development: Python, Java, SQL/MySQL, HTML, CSS, JavaScript, REST APIs, HTTP
Software Engineering & Frameworks: Spring Boot, Hibernate, JDBC, JPA
Data Science & Analytics: Pandas, NumPy, TensorFlow, Scikit-learn, OpenCV, Matplotlib, Seaborn, Statistical Analysis, Data Visualization

Cloud & DevOps: AWS, Kubernetes, Docker, Jenkins, CloudWatch
Monitoring & Observability: Dynatrace, Splunk, ESS, Log Analysis, Telemetry Analysis, Incident Monitoring
Databases: PostgreSQL, MySQL, MongoDB

Certification

AWS Certified Cloud Practitioner

Languages

English: Fluent

Telugu / Hindi: Native

Timeline