Zeeko is a one-stop solution for the Cruise Industry. It contains multiple modules like zPOS, zBook, zView, zQue, zDine, zGalley, zCare which are the apps used to perform various actions on Cruise ships like payment, making reservations, etc.

• Worked on the creation of modules for employee management, guest apps, and waiter apps

• Involved in Database design and modeling in generating structure, normalization, dependencies between tables, and other aspects of the database

• Experience with collaborating with partnering teams and individuals to accomplish common goals

• Worked on finding compatible hardware for POS solutions

• Worked on creating print receipts using the printer language for the module

• Develop modules and applications using Node Js and Java

Express Scripts, USA

Communication Platform is a platform where we reach out to members via different Omni channels like Email, Phone, Text, Letter, etc. to send notifications regarding the Health Insurance.

• Implement and maintain several modules based on SpringBoot microservices and asynchronous communication between them using the Kafka interface

• Generating Metrics Reports by executing scheduled Cron Jobs at Regular intervals in Unix

• Configure and maintain New Relic Dashboards and Splunk Dashboards to track the application performance issues and identify the root cause of underlying issues

• Been a member of the SRE team to provide production support for the application by addressing Incidents in Service Now, handling any urgent issues, and monitoring the application's health

• Involved in Release activities by deploying the release modules to production by working with the Release management

• Reprocessing unsuccessful queries through the Kafka interface and, generating Data zap requests for configuration changes in a production environment

• Use Spring JPA, Spring Security, and Hibernate, to establish and manage database connection pool and leaks, perform data transactions and authorizations

eDiscovery Collection Process includes extracting potentially relevant electronically stored information (ESI) from its actual source and storing it in a target location. Disparate data sources have different levels of accessibility and different collection challenges.

● Involved in sprint planning, task estimation, and resource planning

● Implemented data collection process from disparate data sources including and not limited to Cloud (Facebook, G-Suite, MS Office 365, Dropbox, SalesForce, Box, Slack, JIRA, Confluence), On-premises (Exchange, SharePoint, EMC SourceOne, Enterprise Vault), Offline

● Collection of different data types which includes structured, semi-structured, and unstructured

● Performed targeted collections from the data sources using data filters like date filter service, keyword search service, etc offered by the data source's APIs and SDKs

● Performed data metrics and prepared test data for benchmarking validation and certification

● Designed, developed, and managed REST APIs and microservices

● Stabilized and optimized the bulk / parallel data collection processing with multithreading to achieve concurrency

● Resolved time-out problems when processing large amounts of data

● Developed advanced features for collecting protected documents that are protected with Microsoft Azure Information Protection (AIP) using Powershell

● Resolved highly unstable and sensitive data sources such as enterprise vault

● Participated in enterprise architecture review discussions

● Implemented AWS EC2 and EFS to achieve scalability

● Involved in Incident, Change, and Release Management. Tracked the activities in Kayako ITSM software

● Resolved high-priority problems and responded to critical support tickets on time

● Collaboratively worked in a cross-functional team at geographically distributed locations for successful completion and deployment of projects and providing ongoing support

Electronic discovery is the process of identifying, collecting, and producing electronically stored information (ESI) in response to a request for production in a lawsuit or investigation.

eDiscovery Data Management includes processes like data collection, data review, labeling and categorizing them according to their sensitivity, and producing the relevant files in a desired native format.

● Involved in all the phases of the SDLC using Agile Scrum methodology. Product backlog, Sprint planning, and Project meetings were managed using JIRA and version 1

● Worked with business analysts to understand the user requirements and perform requirement analysis, gap analysis, and feasibility check

● Designed and developed a common framework for easy plug-in of all the connectors to perform the electronic data collection process

● Implemented the code using MVC design pattern

● Used Hibernate framework for object-relational mapping and access to databases. Criteria API and HQL were used for data manipulation in the database

● Designed and developed code in Java/J2EE, SQL, and Cassandra CQL

● Performed data extraction and indexing using third-party libraries such as isys, and Lucene

● Involved in database design, and responsible for CRUD operations in database objects. Stored and managed cache in the Redis database

● Deployed code using CICD pipeline with Jenkins

● Code quality, Code Security, Coding standards, and vulnerabilities were continuously scanned using SonarQube

● Designed test scripts and performed unit testing using JUnit

● Performed regression testing to ensure the application still functions as expected after any code changes, updates, or improvements

● Delivered high-quality backlogs on time, with no regression issues. Utilized log4j and slf4j for logging and debugging purposes

● Managed the identified bugs using Mantis

● Developed orchestration for auto-scaling AWS EC2 Windows & Linux instances with the help of AMI ID configurations