- Designed and implemented an endpoint for customer checkout- Key achievement: Created a pipeline on AWS in order to sent data from S3 to Opensearch index using with SQS, CloudwatchUsed technologies: Java, React, AWS, Docker, Elasticsearch

- Participated in the feature design and implementation phase of the transformation of SAP modules with Java (Spring Boot) and React- Optimized queries and rewrite backend services of monolith project to microservice architecture in order to increase performance- Implemented features of new designs to backend and managed to fix live issues- Key achievement: Optimized and reduced one service response time from ~20sec to ~0.6sec by detecting the issue, coming with the solution and explaining to scrum team and software architectUsed technologies: Java, Spring Boot, Hibernate, Maven, UC4, PL/SQL, OracleDB

- Contributed E2E to search engine products with Python and Vue.js stack- Increased the query coverage ratio up to %98 for responsible service and products, proposed features to PM to increase exposure rates- Implemented Data Module API’s and Data Handlers with Java and Python stack in order to communicate with CP API’s- Contributed as maintainer in backend development team and received “Sparkling Star” award via nomination from HEM of development team for the successful Git Branch Management and tutoring to the newcomers- Led to the Python Ecosystem in Huawei R&D Center, created seminars and sessions, gave trainings about PythonKey achievement: Solved the exposure rate problem on production with configuring the SLB’s. Exposure rate went from ~100 to ~4000 per day for a product

- Developed the widgets of saving potential to convert machine learning models into services and pipelines to be consumed at web scale platform using Node.js and Vue.js- Wrote the technical documentation and presented the saving potential product to the companyKey achievement: Created the new algorithm of the Saving Potential product with machine learning techniques that saves up to %15-20 electricity consumption using Python stack

- Applied the CNN algorithm to the clothing image database, a classifier project with an accuracy rate of 92% was developed- Prepared the dataset and applied the algorithm using MsSQL and Python to extract insights about which products tend to be sell together

- Supported the development part of login component in e-commerce project with PHP