Welcome to my GitHub profile! I'm currently pursuing a Master of Science in Computer Science at the University of Texas at Arlington, with a focus on Cloud Computing, Data Analytics, and Software Engineering. Feel free to explore my repositories and connect with me!

{
  "Programming Languages": ["Java", "Python", "C", "HTML", "CSS", "JavaScript", "TypeScript", "XML", "SQL", "Scala"],
  "Frameworks": ["Node.js", "Express.js", "Firebase", "OpenCV", "Spark", "Django", "Hadoop"],
  "Tools": ["GitHub", "Jenkins", "CI/CD", "AWS", "GCP", "Docker", "Kubernetes", "Snowflake", "Informatica PC", "IICS"],
  "Databases": ["SQL Server", "Cosmos DB", "MariaDB", "MongoDB", "AWS Aurora", "AWS Dynamo DB"],
  "Miscellaneous": ["Excel", "Power BI", "ServiceNow", "TensorFlow", "REST APIs", "Postman"]
}

• Master of Science in Computer Science
  University of Texas at Arlington, TX, USA
  August 2023 - Present
  GPA: 4.0/4.0
  Relevant Courses: Cloud Computing, Design and Analysis of Algorithms, Data Analysis and Modeling Techniques, Software Engineering II, Data Mining, Big Data

• Bachelor of Technology in Computer Science & Engineering
  Mumbai University, Navi Mumbai, India
  August 2017 - July 2021
  GPA: 3.54/4.0

• Data Engineer
  LTI Mindtree
  June 2021 – April 2023
  Responsibilities included analyzing HR data, enhancing data quality, and automating data processes using tools like Snowflake, Python, SQL, and Bash Scripts.

• Software Developer Intern
  SDG- Ramrao Adik Institute of Technology
  May 2019 – July 2020
  Led development and deployment of web projects, involving multiple teams and technology stacks.

React | Next.js | AWS Lambda | TensorFlow | OAuth 2.0

• Led 5 engineers in building a full-stack platform handling 15k+ concurrent users, reducing API latency by 30% through Redis caching and optimized React rendering
• Architected ML recommendation engine using XGBoost that improved user retention by 25%
• Implemented CI/CD with GitHub Actions, achieving 95% test coverage and zero-downtime deployments

Java | gRPC | Docker | Kubernetes

• Engineered 5-node fault-tolerant cluster achieving 99.9% availability during network partitions
• Reduced leader election time to <5s through optimized heartbeat mechanisms
• Simulated 10+ failure scenarios including Byzantine faults, ensuring consistent state replication

GCP | PySpark | React | Terraform

• Automated 20+ data transformation workflows, reducing manual effort by 70% for 150+ enterprise users
• Built secure frontend with chunked S3 uploads handling 100GB+ datasets
• Slashed deployment time 83% (30→5 mins) via GitHub Actions CI/CD and infrastructure-as-code

TensorFlow | AWS CDK | SQS | ResNet-50

• Achieved 94% classification accuracy on ImageNet subset using transfer learning
• Designed event-driven retraining system with SQS queues, reducing model drift by 40%
• Implemented multi-region deployment with auto-scaling groups handling 50+ req/sec

Cloud & Data Engineering

Full-Stack Development

MLOps & DevOps

Thank you for visiting my profile. Let's connect and collaborate on future projects!