Hello, World! 👋
Yash Patel
MS Computer Science @ Illinois Institute of Technology · Software Engineer with 4+ years of experience crafting scalable backend systems, microservices, and event-driven architectures.
$ whoami
const yash = {
role: "Software Engineer",
education: "MS CS @ Illinois Institute of Technology",
location: "Concord, NC",
focus: [
"Distributed Systems",
"Microservices Architecture",
"Event-Driven Design"
],
status: "Open to SWE / Backend roles"
};Software Engineer with 4+ years of experience building scalable, high-availability backend systems using Python and Java across cloud-native environments. Specialized in microservices, event-driven architectures, and distributed systems leveraging Spring Boot, FastAPI, Kafka, and Redis to process millions of transactions. Strong expertise in AWS, Kubernetes, Terraform, and CI/CD automation, ensuring optimal performance and cost-efficiency.
$ cat skills.json
Programming Languages
Backend & Frameworks
Distributed Systems & Streaming
Databases & Caching
Cloud & DevOps
System Design & Engineering
$ git log --work
- Architected event-driven microservices using Java Spring Boot and Apache Kafka to process 8M+ daily transactions, reducing end-to-end latency by 42% and improving system throughput by 35%.
- Engineered high-availability REST and gRPC APIs with FastAPI and Spring Boot, supporting 150K+ monthly active users and achieving 99.98% uptime through resilient retry/circuit breaker patterns.
- Optimized PostgreSQL and Redis caching layers by redesigning data models and indexing strategies, cutting query response times by 55% and lowering database load by 30%.
- Orchestrated containerized deployments on AWS EKS using Docker and Terraform, decreasing provisioning time by 60% and cloud costs by 18%.
- Implemented OAuth2 and JWT API security controls with centralized authentication, eliminating unauthorized access attempts to pass SOC2 audits.
- Automated CI/CD workflows via GitHub Actions and Jenkins, integrating test suites that improved release frequency by 40%.
- Developed scalable backend services in Python and Java, handling 3M+ monthly API requests while improving response consistency by 33%.
- Designed distributed messaging pipelines with Kafka and Redis Pub/Sub for real-time notifications, decreasing event lag by 48%.
- Refactored monolithic modules into containerized microservices using Docker and Kubernetes, accelerating deployment cycles by 45%.
- Constructed optimized SQL queries and indexing across MySQL and MongoDB datasets exceeding 500GB, improving reporting performance by 52%.
- Deployed cloud-native workloads on AWS and GCP leveraging Infrastructure as Code, cutting setup time to under 2 hours.
- Instituted TDD practices with automated test coverage >85%, reducing regression incidents by 31%.
$ ls -la ./projects
Market Sentiment Analysis Engine
Built an NLP pipeline using FinBERT to analyze financial sentiment from 5+ sources and correlate with real-time stock prices. Fully automated ingestion and REST API.
$ cat credentials.txt
AWS Academy Cloud Foundations
Amazon Web Services
VerifiedIntroduction to Networks
Cisco Networking Academy
VerifiedAlgorithmic Toolbox
UC San Diego via Coursera
VerifiedMongoDB in Python
DataCamp
Verified$ ./send_message.sh
Let's Build Something Great
I'm actively looking for Software Engineering, Machine Learning Engineering, and Data Engineering roles. Whether you have a question, opportunity, or just want to connect — my inbox is always open.