Brajesh Shishir

Software Engineer

Bengaluru, Karnataka, India7 yrs 8 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

Stackforce AI infers this person is a Backend-focused Software Engineer with expertise in Cloud Computing and Machine Learning.

Database Management System (dbms)Apache KafkaObject-oriented Programming (oop)Machine Learning

Azure Cosmos DBKafkaRedisZookeeperspring-boot micro-servicesCore JavaSAP UI5JavaScriptApache CamelCLinuxMATLABMLNeural NetworksJava

7 yrs 8 mos

Total Experience

2 yrs 6 mos

Average Tenure

4 yrs 6 mos

Current Experience

Nov 2021 – Present · 4 yrs 6 mos · Bengaluru, Karnataka, India

Azure Cosmos DBDatabase Management System (DBMS)

Dec 2019 – Oct 2021 · 1 yr 10 mos · Bengaluru, Karnataka, India

OCI(Oracle Cloud Infrastructure) Data Integration
Worked as Backend developer in OCI(Oracle Cloud Infrastructure) for developing a multi-tenant service(Data Integration Service) as part of Big Data platform.
Developed a distributed system for execution of tasks under heavy message load scenarios using distributed cache and message brokers.
Worked on open source technologies like Kafka, Redis, Zookeeper, spring-boot micro-services.

KafkaRedisZookeeperspring-boot micro-servicesApache KafkaDatabase Management System (DBMS)

Jul 2018 – Nov 2019 · 1 yr 4 mos · Bengaluru Area, India

SAP Cloud Platform Integration (SAP CPI):
Worked as a Full Stack Developer for developing a Design-time graphical modeling tool for ‘SAP CPI’. The tool provides seamless connectivity between cloud applications and other SAP and non-SAP enterprise software. It allows users to design integration scenarios, deploy and run them on cloud platforms.
Technology Used:
o Development : Core Java, SAP UI5, JavaScript
o Runtime: Apache Camel

Core JavaSAP UI5JavaScriptApache CamelObject-Oriented Programming (OOP)Database Management System (DBMS)

Jul 2017 – Dec 2017 · 5 mos · Bengaluru Area, India

Configured NVMe-of target and explored its multi-streaming capabilities.
Explored various algorithms to support multi-streaming like, MQ(Multi-Queue) and SFR(Sequentiality Frequency Recency).
Technology Used : C, Linux

CLinux

May 2015 – Jul 2015 · 2 mos · New Delhi Area, India

Predicted the future values of GDP, Reserve Money, Narrow Money and Broad Money of India using Machine learning concepts
Implemented the concepts of Artificial Neural Networks (Error Back propagation, Gradient Descent and Dynamic Tunnelling) for time series prediction of the above using Multilayer Perceptron (MLP).
Technology used: MATLAB, ML, Neural Networks

MATLABMLNeural NetworksMachine Learning