Ayush Tiwari

Software Engineer

Bengaluru, Karnataka, India5 yrs 10 mos experience

Most Likely To Switch

Key Highlights

5 years of backend development experience.
Expert in developing scalable and secure applications.
Proven track record of optimizing database performance.

Stackforce AI infers this person is a Backend Developer with expertise in SaaS and Healthcare applications.

Contact

atiwari13@wayfair.com +919479906061 LinkedIn

Skills

Core Skills

JavaGcpNodejsKafkaSqlJavascriptReactPython

Other Skills

AlgorithmsAnalytical SkillsBack-End Web DevelopmentCC++Code ReviewConvolutional Neural Networks (CNN)Data StructuresDeep LearningExpressJSGITGOLANGGitGo (Programming Language)Google BigQuery

About

As a backend developer with 5 years of experience, I have a solid foundation in computer science and expertise in developing robust, scalable, and secure applications. I graduated from NIT Srinagar with a degree in Computer Science and Engineering and have since worked with some of the most innovative companies in the industry. My skills and knowledge span a broad range of programming languages and tools, including JavaScript, Java, Python, NodeJS, SQL, NoSQL and GCP. I am adept at designing and implementing RESTful APIs, integrating with third-party services, and optimising database performance. Additionally, I have a keen eye for detail and am committed to delivering high-quality code that meets project requirements and exceeds client expectations.

Experience

5 yrs 10 mos

Total Experience

1 yr 11 mos

Average Tenure

2 yrs 10 mos

Current Experience

Wayfair

Software Engineer 2

Aug 2023 – Present · 2 yrs 10 mos · Bengaluru, Karnataka, India · Remote

Developed supplierfacing applications visualizing supply chain forecasts with optimized Google BigQuery queries, ensuring a fast and smooth user experience through close collaboration with data engineering.
Built an inbound order creation system portal for suppliers, handling both backend and frontend development to simplify stock planning, improve forecast visibility, and enable bulk actions
Designed and developed a Kafkabased notification system to alert suppliers of inventory errors, automating compliance checks and error tracking, cutting manual followups.
Leveraged Knowledge in Java, Spring(MVC), Python, GraphQL, ReactJS, GCP, Kafka, Kubernetes, SQL.

JavaSpring(MVC)PythonGraphQLReactJSGCP+3

Sharechat

Software Engineer

Sep 2021 – Aug 2023 · 1 yr 11 mos · Bengaluru, Karnataka, India · Remote

Developing and maintaining APIs that served thousands of requests everyday, ensuring high availability and fast response times.
Implementing real-time data processing pipelines to enable our sales team to make data-driven decisions, resulting in a 15% increase in revenue.
Collaborating with the front-end team to build a seamless user experience for our customers.
Collaborated with multiple eCommerce partners to design and implement an app tagging feature, enabling creators to tag shopping products in their posts.
Developed a campaign analytics tool to analyze and track campaign performance on Moj App.
Led a team of 3 programmers to revamp the code for multiple microservices, resulting in a 30% cost reduction.
Utilized expertise in NodeJS, GOLANG, GCP, Kubernetes, SQL, and no-SQL to achieve project objectives.

NodeJSGOLANGGCPKubernetesSQLNoSQL

Optum

Software Engineer

Aug 2020 – Sep 2021 · 1 yr 1 mo · Gurugram, Haryana, India

As a MERN Full Stack Developer, I was a part of the SEG team.
Designed and developed an improved broker tool that streamlines the process of quoting, enrolling, and renewing fully insured Oxford Small Business, making it faster and more efficient.
Spearheaded the implementation of Unit Test Integration across all services to achieve better code coverage and minimize the risk of bugs.
Proficiently utilized my expertise in JavaScript, React, Hooks, Redux, React Router, NodeJS, ExpressJS, and GIT.

JavaScriptReactHooksReduxReact RouterNodeJS+2

Indian institute of science (iisc)

Research Intern

Dec 2018 – Feb 2019 · 2 mos · Bengaluru Area, India · On-site

As a research intern in deep learning, our primary focus was to tackle the challenge of identifying and classifying vehicle damages, a task that could streamline the insurance claim process for both the insurance company and the clients. Through the use of cyclic learning rates, data augmentation, and transfer learning, we achieved an impressive accuracy rate of 96.37%. Our work involved utilizing our expertise in various tools and technologies such as Python, Pytorch, and Keras.

PythonPytorchKeras