Shikher Garg

Software Engineer

Bengaluru, Karnataka, India8 yrs 10 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

Designed and launched CIV4 reports feature for Amazon.
Developed recommendation micro-service using AWS Personalize.
Delivered internal product from scratch at Peak.

Stackforce AI infers this person is a Backend Engineer with expertise in E-commerce and AI/Analytics.

Contact

Skills

Core Skills

ScalaAwsJavaNode.jsMicroservicesAngular.js.net

Other Skills

.NET FrameworkAB TestingAWS API GatewayAWS EMRAWS ElasticSearchAWS LambdaAWS PersonalizeAWS Step FunctionsAirflowAmazon Web Services (AWS)Apache SparkApache SupersetCC#C++

About

I am a competitive programming enthusiast and been doing it for the last 1 years. I am a frequent coder at CodeChef, InterviewBit, HackerRank. Here are some of the sites on which I have worked till now https://www.codechef.com/users/gauravjp50 https://www.interviewbit.com/profile/shikher_garg https://www.hackerrank.com/shikher123

Experience

8 yrs 10 mos

Total Experience

3 yrs 5 mos

Average Tenure

8 yrs 10 mos

Current Experience

Amazon

Software Development Engineer 2

Mar 2022 – Present · 4 yrs 3 mos · Banglore

Working as a SDE-2 with the Associates Analytics Team, where the team's primary role is to produce a variety of reports for Amazon's affiliate partners.
Designed and launched CIV4 reports feature world-wide. CIV4 reports allow associates to examine their content performance based on many characteristics such as content page, amazon links, traffic source, campaign, etc. These reports are used by 10,000+ managed associates. The reports workflow was build on Scala, Spark, AWS EMR and Airflow.
Re-architected the download reports feature on the Amazon affiliate portal with two main objectives: Firstly, adopting AWS ElasticSearch to replace old self managed ElasticSearch, and secondly, to move the old flow to AWS Step Functions.
Migrated TMT's Redshift cluster from DS3 to RA3 nodes with zero data loss and minimal downtime.
I was the POC for Amazon Prime Day for the team, with responsibilities including monitoring, load testing, capacity planning, and ensuring operational readiness of all services for the Prime day.
Developed a Spark job and a Java API to expose the top products and categories to associates in the Creator App.
Implemented an SLA and reconciliation mechanism using AWS Lambda functions to validate the timeliness of S3 reports generated by Spark jobs and reconcile the data with the source team.
Migrated ARS(Analytics Reporting Service) AWS infrastructure code from CDKV1 to CDKV2.
Managed a Support Engineer to complete the Operational Excellence tasks for the team.
Mentored an SDE Intern in the migration of all Data Pipelines from AWS Data Pipeline Managed Service to AWS Airflow.

ScalaSparkAWS EMRAirflowAWS ElasticSearchAWS Step Functions+2

Traveloka

Software Engineer

Oct 2020 – Mar 2022 · 1 yr 5 mos · Bengaluru, Karnataka, India

Worked as a Backend Engineer(Java) with the Recommendation Team, which provides recommendation to various BU.
Designed and implemented a micro-service and a data pipeline using Java to deliver the most frequently issued recommendations for various products such as hotels, food delivery, and experience based on Geo-Location and number of days as parameters.
To increase user engagement on the platform, I designed and implemented a pipeline to give personalised recommendations to users across different product verticals using AWS Personalize machine learning model.
Implemented AB Testing to deliver recommendations based on the user context. It also assists the product team in evaluating user activity based on the recommendations displayed.
Implemented caching and made things asynchronous whenever possible to de-bottleneck microservices and increased the throughput of some of the microservices by 50%.
Implemented rate-limiting for various clients and products by utilizing an AWS API Gateway.
Assist the team in migrating a microservice responsible for displaying cross-sell products from a shared AWS account to a team-specific account.
Implemented a feature that displays recently viewed products.
Automate the retraining of aws personalise modal using a AWS State machine.
Worked on the Recommendation engine for product cross-sell and rule base user targeting

JavaAWS PersonalizeAB TestingAWS API GatewayAWS

Peak

Software Engineer

Dec 2018 – Oct 2020 · 1 yr 10 mos · Greater Jaipur Area

Worked on different Data pipelines that power Peak.ai AI System.
Worked on a feature Workflow that provides infrastructure and provides graphical interface to visualize the components of a data modal as a series of steps to our data science team.
Integrated Apache Superset an analytics tool into Peak.ai AI System.
Written serverless lambda functions in node.js to communicate with client-side architecture.
Implemented caching by utilizing amazon cloud font CDN, and caching on API gateway for API responses.
Contributed to different microservices that power Peak.ai workflow.
Delivered an internal product (Portfolio Management System) from scratch.I was responsible for its complete development frontend as well as backend.

Node.jsApache SupersetAWS LambdaMicroservices

Nagarro

Software Developer Internship

Jan 2018 – Sep 2018 · 8 mos · Gurugram, Haryana, India

Worked on existing Financial application for Blackbaud one of its client where I contributed to its client side in angular.js and worked on its server side rest apis endpoints in Dotnet.
Developed several applications using Node.js , Angular 6 ,Vue.js and Dotnet as a part of training.
Developed a Microblogging Site where users could follow each other and share tweets. Its backend was in Dotnet and frontend was in Angular.js.

Angular.jsNode.js.NET