Devops Engineer Aws

AKHILA MEENAKSHI BAPANAPALLI

AWS DevOps Engineer Email: ***********@***.*** Phone: +1-667-***-**** Portfolio Address: Tampa, Florida-9607 LinkedIn PROFESSIONAL SUMMARY

AWS DevOps Engineer with 2.5 years of experience in DevOps and Backend Development, specializing in AWS, Java, Spring Boot, CI/CD Pipelines, and Cloud Automation. Expertise in containerizing applications, automating deployments, and managing ETL workflows, reducing deployment time by 40 hours per release cycle and improving system efficiency by 30%. Proven ability to implement scalable cloud solutions, streamline development workflows, and optimize infrastructure performance to ensure high availability and security. WORK EXPERIENCE

Magnizent Technologies, India, AWS DevOps Engineer (Jun 2021-July 2023) & Software Developer Intern (Jan 2021- May 2021)

• Containerized applications using Docker, ensuring consistency across environments and reducing deployment failures by 12 hours per month.

• Developed automated CI/CD pipelines using GitLab and AWS Airflow, cutting deployment time by 40 hours per release cycle.

• Designed and implemented DAGs in Apache Airflow, automating ETL workflows and saving 23 processing hours per week.

• Configured scheduled intervals for DAGs, ensuring 99.9% workflow execution accuracy and eliminating 5+ hours of manual intervention per week.

• Integrated GitLab for version control, reducing code conflicts by 8 hours per sprint.

• Deployed and managed Apache Airflow on AWS, optimizing performance and reducing execution time by 15 hours per month.

• Developed and maintained a backend payment module for an online electricity payment system, saving 18 hours per month in manual transaction handling.

• Optimized Java Spring Boot microservices to handle high-traffic transactions, reducing processing time by 10 hours per month.

• Integrated SonarQube for code analysis, improving code quality and eliminating 6 hours per sprint spent on manual debugging.

• Implemented Docker for deployment automation, ensuring consistent builds and reducing infrastructure inconsistencies by 12 hours per month. EDUCATION

Master’s in Computer Science – University of South Florida (Aug 2023 – May 2025) GPA: 3.48/4 ACADEMIC PROJECTS

Automated Deployment of Java Web Application (Jan 2024 – May 2024)

• Developed a CI/CD pipeline using Jenkins, Docker, and AWS, streamlining deployment processes.

• Automated Docker builds and image deployment to Docker Hub & AWS EC2, reducing manual efforts.

• Optimized deployment time by 40+ hours per release through automated build and deployment triggers. Splitwiser – Multi-Currency Expense Tracker (Aug 2023 – Dec 2023)

• Designed a real-time currency conversion system, eliminating 11 hours of manual calculations per week.

• Developed a React-based frontend with a Node.js backend and optimized MySQL queries for faster transactions.

• Conducted usability testing with 32 participants, leading to a 15% increase in user engagement.

• Improved database efficiency, reducing query execution time by 200ms per transaction. Expense Tracker – Python, Flask, PostgreSQL (Jan 2022 – March 2023)

• Developed a web-based expense management system with custom categories and real-time tracking.

• Increased data processing efficiency by 8 hours per month through optimized database design.

• Enhanced user savings by 2 times by implementing smart budget tracking and analytics features. SKILLS

• Cloud & DevOps: AWS (EKS, S3, IAM, Lambda), Docker, Kubernetes, Terraform, Jenkins

• Backend Development: Java, Spring Boot, Microservices Architecture

• CI/CD & Version Control: GitLab, GitHub, Bitbucket, AWS Airflow, SonarQube

• Testing & API Management: Postman, Swagger, REST APIs

• Monitoring & Security: SonarQube, CloudWatch, Log Management CERTIFICATIONS

• Microsoft Azure Fundamentals (AZ-900)

• Google Cloud Digital Leader (GCDL)

• AWS Certified Cloud Practitioner (CLF-01)

AWARDS AND ACHIEVEMENTS

• Reduced deployment cycle time by 40 hours through optimized CI/CD automation.

• Increased data processing efficiency by ~3X times with automated DAGs in Apache Airflow.

• Reduced deployment failures by 35% by implementing containerization and CI/CD improvements.

• Enhanced system security, saving 12 hours per month using SonarQube and best DevOps practices. REFERENCES

• Available upon request

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