successful projects I have worked oN

Objective: Migrate Large Scale data from on-premises to AWS.

Role:

✔ I completed migration of IoT data to AWS Cloud for a large elevator manufacturer in Europe. The migration involved using EMR, spark, AWS Lambda, SQS, EC2, IAM, Kinesis, S3, DynamoDB, Step functions, VPC, AWS Organization, LZ, Python, Typescript, Docker, Gitlab scheduler, Cloudformation, CDK, splunk and updating the data pipelines and applications to use the cloud services.  

✔ Committed to financial efficiency, I applied FinOps principles and conducted cost optimization for the backend system utilizing tools such as AWS Cost Explorer, AWS Budgets, and AWS Trusted Advisor, effectively implementing the derived insights.

✔ Planned and designed AWS Backup and Disaster Recovery Strategy for DynamoDB, Opensearch service.

✔ Additionally, I contributed to successful completion of the ISO-27001 certification audit. This achievement affirmed the quality and security of the software, demonstrating commitment to excellence.

Outcome: Improved application performance and scalability and 30% reduction in operation costs.

Objective: Backend Data Processing and API service for Autonomous Driving system

Role:

✔ Developed and deployed an Azure native backend API service and big Data Processing for data analytics for an AI-driven, Autonomous driving system startup based in the US. The platform allows the startup to collect and analyze data from their intelligent driving system using various sensors and cameras. It also provides driver assistance, collision avoidance, and performance insights. I was responsible for designing and developing cloud solutions using Azure services and Implementing and managing cloud infrastructure and policies.

✔ The design, development and implementation involved ETL, Azure Functions, Azure DB for postgreSQL, VM, Azure container service & registry, API management, Azure backup, REST, Python, Docker.

Outcome: Enabled real-time insights & decision-making resulting in 25% (approx) increase in operational efficiency.

Objective: Design Backend system Integration & API management for streaming data to support predictive analytics and remaining useful life of spare parts. 

Role:

✔ Designed and implemented a AWS cloud backend service for data analytics platform for a large OEM. The platform allows the vehicle manufacturer to collect and analyze data from their vehicles and customers using various sensors and devices. The platform also provides features such as predictive maintenance, customer segmentation, and personalized recommendations.

✔ I was responsible for designing and developing cloud solutions using cloud-native AWS services, such as serverless framework, lambda, Python, Flask, Java, Docker, MongoDB, AWS SAM, Cloudformation, AWS Batch, SQS, IAM, EC2, ECR, Cognito, API Gateway, REST, Python, Docker, and Sonarqube.

✔ Enabled AWS Infrastructure for machine learning platform and collaborated with data scientists to deploy models in scalable and efficient manner.

Outcome: Enabled customer to predict the remaining useful life of spare parts and optimize inventory management leading to 15% increase in sales approx.

Objective: Distributed Microservices and API Management for Asset management platform that provides real-time tracking, predictive maintenance, and ride-sharing for a fleet of commercial vehicles.

Role:

✔ Created an asset management platform microservices that is a cloud agnostic (multi-cloud) backend system for telematics analysis, ride sharing and connected vehicle tracking and management for an Indian MNC. The platform allows the users to monitor and manage their vehicles and assets using a web dashboard and a mobile app. The platform also provides features such as geofencing, fuel consumption, driver behavior, and maintenance alerts. I was responsible for:

✔ Designing, data modeling and implementing cloud solutions using AWS, and PostgreSQL

✔ Implementing and managing cloud infrastructure, policies and controls using Keycloak, AWS CloudFormation and Gitlab CICD.

✔ Developing and deploying microservices using Java, Spring Boot, python, flask and Docker

✔ Implementing and managing the telematics data analysis and visualization using Elasticsearch and Kibana

✔ Monitoring and performance optimization of the API using AWS CloudWatch and JMeter

✔ Analyzing and evaluating technical debts, tools and frameworks such as kong, Jhipster gateway

✔ Code review and mentoring junior peers

Outcome: Enabled asset management platform for efficient and scalable shared mobility services.

Objective: AWS Serverless Backend API Integration Service & API Management for cross-company collaboration to detect vehicle accident for insurance claim

Role:

✔ I set up a cloud backend integration service for a Japanese four-wheeler insurance company that enables cross-company collaboration and data exchange.  

✔ Create API that integrates with Third party API for data exchange and manage the data for real-time insight gain and reports.

Outcome: Successful and efficient integration increasing the insurance claim process by approx 15%

Objective: Distributed Microservices and API Management for Two-wheeler Ride Navigation System

Role:

✔ I implemented multiple microservices for a two-wheeler tracking and navigation system that uses Oauth2.0 for security and cloud agnostic backend API management for an MNC. The system allows the users to track and navigate their two-wheelers using a mobile app and a GPS device. The system also provides features such as theft detection, emergency alert, and ride history. I was responsible for:

✔ Designing and Implementing the security system using Oauth2.0 providers, such as Keycloak and Auth0

✔ Designing and implementing backend system using AWS and GCP services, such as EC2, S3, Cloud Functions, Cloud Storage, etc and using tools  such as Nomad, Consul, Redis, Graylog, Zipkin.

✔ Developing and deploying microservices using Java, Spring Boot, Jhipster and Docker

✔ Integrating with third-party APIs and services, such as Google Maps and Auth0.

Outcome: Successful delivery of the services with an excellent customer satisfaction score of above 90%

Objective: Re-Platforming & Development of Data Analytics & Conversational AI product in AWS

Role:

✔ Designed a distributed backend system and cloud architecture for a conversational analytics platform for mid-sized company. It is a conversational analytics platform that provides intelligent and actionable insights from voice and text data.

✔ Completed Audio-preprocessing and algorithms on data cleaning to enable Job processing to extract insights from the large-scale data

✔ Integrating with API services like Google speech-to-text AI, using kafka for streaming data and adopt Java concurrency for seamless processing and storage in SQL DB.

Outcome: Increased speed and operations by 25% with agile mastery of product lifecycle.

Technical Skills

✔ Programming Languages: Java8+, Python, TypeScript

✔ Cloud Platforms: AWS, Azure, GCP

✔ Frameworks: Spring Boot, Flask, Jhipster, Serverless Framework, Django

✔ DevOps Tools: Jenkins, GitLab, Docker, Cruisecontrol, AWS SAM, CDK

✔ Database and Analytics Tools: Microsoft SQL, PostgreSQL, MongoDB, DynamoDB, Spark, Jupyter

✔ Other Tools & Frameworks: Keycloak, Auth0, Okta, Splunk, Eclipse, Vscode, Pycharm, Graylog, Consul, Jmeter, Sonarqube, Kafka, Pytest, PlantUML, Swagger, Postman, curl

✔ Operational system: windows, Linux(ubuntu)

✔ Methodologies: Scrum, Kanban, Agile, ZDD(Zero defect delivery), TDD(Test driven development), CICD

Business Data Analysis Skills

✔ Data Visualization: PowerBI

✔ Data Modeling & Architecture Designs: PlantUML, SchemaSpy, Draw.io 

✔ Requirements Elicitation: Jira, Confluence

✔ Stakeholder Management: Communication, Negotiation, Collaboration

Soft Skills

✔ Communication: Fluent in English and Tamil, able to communicate effectively with clients and team members, both verbally and in writing.

✔ Collaboration: Experienced in working with cross-functional and distributed teams, using agile methodologies such as Scrum and Kanban.

✔ Leadership: Able to lead and mentor junior developers, provide feedback and guidance, and delegate tasks.

✔ Time Management: Able to prioritize and manage multiple tasks, meet deadlines, and deliver quality results.

✔ Problem Solving: Able to analyze and solve complex and new business problems, using logical and creative thinking.