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Software Engineer with 8+ years of experience in design and development of enterprise applications.Has vast knowledge in Retail Financial and Logistics domain. Appreciated for series of successful releases and for quick turnaround in providing sol...
Artificial Intelligence - ChatBot, Google Dialog Flow (NLP Engine)
Big Data (Intermediate) - Spark, pyspark , Hive, Hbase, Kafka and Drill
Integration technologies - SOAP, REST, EIP, Axway and Apache Camel
JEE - EJB 3.x, MDB
Frame Works - Struts 2, Hibernate 3.0, JTA, JPA, Spring 3+ and Spring Boot
Server - Apache tomcat and JBOSS Application Server
ESB - Mule ESB and JBOSS Fuse ESB
IDE - Eclipse and IntelliJ IDEA.
Source control - SVN and GIT
Bi Model - Micro Services using Openshift, Docker
Database and tools - Mysql, MS SQL server. Oracle, Cassandara and Mongo (No SQL)
Development technologies - Agile and WaterFall Methodology
Continuous Integration and Delivery - Jenkins and UrbanCode
Build Tools - Maven, Gradle and Ant
Cloud - Google Cloud Functions, Amazon SQS, Amazon S3 Bucket, Amazon EC2 and Amazon Web Services
Collaboration - JIRA, Redmine and Confluence
Other tools and technologies - Putty, Quartz, Linux, Jasper, JMeter, JConsole, JASS/LDAP, PMD and Freemarker.
Networking & Security
Data & Analytics
Virtual Assistants (AI)
- Worked on VA platform which will forward requests from the channels you desire to your bot application
- Worked on creating dialog flow agents which act as a Natural Language Process (NLP).
- Worked on Backend application which integrated back end application with chat bot using NodeJS and Java
- Integrated multiple channels like, Facebook messenger, slack, Alexa and slack
- Developed analytics tool which will give report about the Chabot related statistical data and analysis using Python
- Implemented on Human take over, Download chat history in PDF and Feedback responses
- Deployed in cloud using Google cloud functions and manage all the application using separate dockerized container platform.
ToolsVisual Studio (Win) PyCharm
Fully Landed Costs (FLC)
- Worked on data load data from aptean.
- Worked on all calculation logic part by supporting multiple formulas and condition.
- Implemented adding different unit of measure in all fields.
- Worked on multiple currency and conversion supported by application.
- Deployed many services in docker based on Micro services architecture
- Worked on performance side improving memory and reduce the api response to 3 milliseconds.
EzyCommerce (EZC) is an automated e-commerce fulfillment offering aimed at Small and Medium Enterprises (Merchants) in Asia Pacific to help them sell online, with increased productivity. As Merchants establish online presence and increase the number of online sales channels, EZC helps them to scale by outsourcing end to end fulfillment process to a trusted, reliable and cost-efficient service provider like Singpost. Using EZC, Merchants can manage orders from multiple online sales channels using a single platform and get access to world-class fulfillment capabilities.
Connect to online sales channels: Merchants can connect seamlessly with their existing order capture systems such as marketplaces, shopping carts or use semi-automated methods such as file uploads for order submission to the ezyCommerce platform
- Developed many camel routes which used send messages to different systems.
- Inbound/Outbound fulfilment orders received from online sales channels
- Worked on Ebay, Shopify and Amazon API services to connect online sales
- Involved in creating Blueprint and spring type camel routes.
SkillsMule ESB Java (All Versions) Spring Framework SQL AWS AWS S3 Jenkins Docker Apache Camel JBoss
Roles and Responsibilities:
- On call 24/7 as a L3 engineer.
- Worked with a team of 5 engineers to build in house capabilities to administer and monitor full thousands of Hadoop nodes.
- Deeply instilled DevOps culture across a 100+ sized engineering team and moved away from 3 months release cycle to a 1-click release.
- Identify various data product use cases, data sources and governance requirements
talking to business stake holders
- Developed data application using Spark as the processing layer to deliver analytical
Power BI reports to Clients
- Design and implement robust data pipeline for real-time analytics stream processing and machine learning with MapR platform and Spark Structured Streaming
- Performed Data ingestion to DL platform with many Data sources like mysql, oracle and MSSQL
- Involved in Both Real Time and Batch Data
- Work with data science team in implementing churn prediction models with SparkML
- Automate deployment workflows with Jenkins and docker
- Created and scheduled spark jobs in Airflow
SkillsHadoop Spark Streaming PySpark Java (All Versions) Apache Spark Apache-Kafka Hive HBase Drill Jenkins Docker