Dhruv Shah · Java Backend · Spring Boot · AWS · Amazon Connect
A focused portfolio page showing how I apply AWS cloud concepts to backend systems, serverless workflows, contact center automation, security, observability, and reliable application infrastructure.
Java backend foundation with hands-on AWS cloud practice.
AWS Mumbai
AWS Mumbai learning experience
Attending the AWS event in Mumbai gave me a closer look at how cloud platforms support large-scale, reliable, and low-latency systems.
One session that stood out focused on Disney+ Hotstar's architecture and the engineering decisions behind serving millions of concurrent users during peak traffic.
The event helped me connect AWS services with real production concerns such as scalability, availability, performance, monitoring, and cost-aware infrastructure.
It also gave me a stronger appreciation for how cloud engineers think about system design beyond just deployment. I left with clearer direction for my own learning: build stronger backend systems, understand cloud operations deeply, and keep improving my ability to design reliable applications on AWS.
AWS Transform sessionMulti-agent systems talkSummit floor perspectiveAWS Village floor
Profile
Java backend foundation with AWS cloud focus
This page highlights how I connect Java backend engineering with AWS cloud concepts across services, APIs, data storage, Amazon Connect, security, monitoring, and deployment patterns.
My strongest foundation is Java backend development with Spring Boot, REST APIs, SQL, authentication, and reliable service design. AWS is where I am building practical experience in deploying, securing, observing, and scaling those systems in cloud environments.
Understanding how backend applications run inside secure cloud networks using EC2, VPC concepts, load balancing, access control, and deployment environments.
Lambda / API Gateway / Events
Serverless Integration
Using Lambda, API Gateway, and event-driven workflows to connect backend services, automate tasks, and support lightweight cloud integrations.
SQL / RDS / DynamoDB
Data-Aware Systems
Mapping application needs to the right storage patterns across S3, RDS, DynamoDB, operational records, and analytics-ready cloud data.
IAM / KMS / CloudTrail
Security Posture
Applying least privilege, encrypted secrets, IAM policies, KMS, CloudTrail, and access controls to support secure cloud systems.
CloudWatch / Budgets / Config
Operational Visibility
Looking beyond deployment with logs, metrics, alerts, budgets, configuration checks, and systems that are easier to debug and maintain.
Spring Boot / REST APIs / SQL
Java Backend Engineering
Building from a Java-first base with Spring Boot services, REST APIs, SQL, testing, authentication, and reliability patterns that can move confidently onto AWS.
Cloud Data Engineering
Cloud data engineering experience that informs my AWS approach
My cloud learning is supported by real internship experience with industrial data movement, pipeline reliability, and cloud migration work. At Larsen & Toubro Heavy Engineering, I supported data modernization efforts involving on-premises IoT warehouse environments and Azure cloud platforms.
This experience helped me understand practical cloud concerns such as ingestion, transformation, validation, storage design, reporting, and operational visibility. Even though the project used Azure, the same engineering mindset applies to AWS services such as S3, Glue-style pipelines, RDS, DynamoDB, and analytics workflows.
Industrial data pipeline support
My cloud learning is supported by real internship experience with industrial data movement, pipeline reliability, and cloud migration work at Larsen & Toubro Heavy Engineering.
Data transformation and quality
This work helped me understand practical cloud concerns such as ingestion, transformation, validation, storage design, reporting, and operational visibility.
Pipeline reliability practices
Even though the project used Azure, the same engineering mindset applies to AWS services such as S3, Glue-style pipelines, RDS, DynamoDB, and analytics workflows.
Transferable cloud concepts
The experience reinforced how cloud systems need reliable movement, validation, visibility, and repeatable operations across platforms.
Amazon Connect
Amazon Connect and customer experience systems
I am building hands-on understanding of how Amazon Connect supports cloud-based customer communication systems. My focus is on contact flows, routing, queues, Lambda integration, customer context, observability, and smoother support experiences.
Amazon Connect Lab
Intent → Route → Resolve
Planned proof-of-concept
A proof-of-concept flow where a customer request enters through Amazon Connect, routes to the right queue, triggers Lambda-backed logic when useful, and creates operational signals through contact records and CloudWatch.
01 / Contact Flows
Contact flows with clear customer paths
Designing IVR and chat flows around prompts, queues, business hours, fallback handling, transfers, and simple routing decisions.
02 / Backend Integration
Lambda-backed service actions
Connecting Amazon Connect with Lambda so customer intent can trigger lookups, validations, lightweight APIs, and self-service actions.
03 / Routing Logic
Queue and routing awareness
Understanding queues, routing profiles, agent handoff, customer context, and the operational details that make support smoother.
Credentials and Progress
Certifications and preparation progress
Backend / Spring Boot
Master Spring Boot 3, Spring AI, Spring Security, Docker, & Cloud Deployment to build modern enterprise applications
I am early in my career, but I focus on the habits that help teams trust me quickly: learning the system, asking clear questions, taking ownership of scoped work, testing carefully, documenting decisions, and communicating progress.
Backend Development
Contribute to Java and Spring Boot services, REST APIs, validation logic, SQL-backed workflows, and maintainable backend code.
Cloud Support
Support cloud tasks around IAM, deployments, monitoring, documentation, and environment configuration under team guidance.
Troubleshooting
Use campus IT and support experience to diagnose issues clearly, communicate with users, and escalate with useful context.
Documentation
Write clear notes, setup guides, runbooks, and project documentation that help teams move faster and reduce repeated questions.
Working Style
How I work with teams
Listen
Understand team needs
Learn workflows, tools, customer priorities, and what the team considers a good solution.
Build
Take scoped work seriously
Contribute to backend, cloud, support, or documentation tasks with careful testing and clear communication.
Improve
Keep raising the bar
Use feedback to improve quickly and look for small ways to make systems easier to understand, run, and support.
06 / Contact
Let’s talk backend and cloud engineering
I am open to backend engineering, software engineering, cloud engineering, data engineering, and customer experience technology roles where I can contribute to reliable systems and keep growing.