Sep 2021 – Dec 2022 · 1 yr 3 mos · Seattle, Washington, United States

• Worked as Senior SDE in Payments team

Sep 2019 – Aug 2021 · 1 yr 11 mos · Greater Minneapolis-St. Paul Area

• Build price management platform for managing prices of all items sold in ∼1800 stores and online channels. Pricing platform consists of three parts - price ingestion from 30 different sources, price processing and optimization derived from various signals and publishing prices to upstream systems(website and stores channel).
• Build rules processing engine to derive price for requested item at location by configuring all business related rules at one place. Exposed APIs to provide capability of stateless computation of prices to merchants, analysts and other teams. Prices of all items sold in Target (stores/online) were computed using this component. Normal web traffic is 5000 requests per second with 100X load during peak season.
• Tech Stack: Java 8, Spring boot, Junit, Gradle, Docker, Kubernetes, Hibernate, Oracle, Postgres, Redis, Kafka, MongoDB

Sep 2018 – Jan 2019 · 4 mos · Greater Chicago Area

• Database Programming (MySQL/Oracle)

Jun 2017 – Aug 2018 · 1 yr 2 mos

• As a part of the Target Competitive Intelligence Pricing team, I worked on -
• ◦ Design and developed service oriented architecture (SOA) based microservices for recommending competitive sensitive price of items sold in Target stores by ingesting requested crawled price into our platform which goes through series of multiple REST based microservices to enrich and derive competitive prices of target items from competitor prices. Web Traffic on the platform was 3000 Request per second.
• ◦ Build competitive pricing cluster management platform which identifies the relationship between target stores and competitor (Walmart) stores by plotting latitude and longitude coordinates of all ∼1834 Target US stores and competitor stores on Google maps and storing all dependent factors in database such as price variability of item, availability of item in region etc. which helps in deriving corresponding competitor stores from pricing cluster.
• ◦ Improved business metrics of low return rate by filling in pricing gap by 18% of 100+ items by proposing and implementing competitive pricing algorithm for those items whose corresponding competitor(Walmart) price points were unavailable in specific regions of US.
• Tech Stack -Springboot, Gradle, Kafka, Elasticsearch, Oracle, Java 8, Reactive Java (RxJava), Redis, Docker, Kubernetes, drone, Junit, Git

Sep 2016 – May 2017 · 8 mos

• As a part of the Target Search platform team, I worked on -
• ◦ Revamped target.com enterprise search platform to microservices based architecture (APIs and batch process) from monolithic architecture by creating data ingestion pipeline from 25 different data source/team such as items, prices, inventory etc at different time of day via Kafka/REST-endpoints through distributed Springboot batch applications which indexes in Apache Solr.
• ◦ Exposed REST endpoints using Solr java client on the top production Solr cluster for returning search results for incoming customer's web search request from target.com and target iOS app. (Web Traffic on platform was ~5000 Request per second)
• Tech Stack - Springboot, Gradle, Apache Solr 6, Zookeeper, Spinnaker, Kafka, Java 8, Junit, Design Patterns

Jun 2016 – Aug 2016 · 2 mos · Bengaluru, Karnataka, India

• Part of the Ekart Logistics team.
• · Real-Time Dashboard - Built real-time dashboard which provided ground-level logistics visibility of customer orders to warehouses hub manager across the entire nation. This was done by consuming order and item level attributes from various Kafka topics and ingest them in Elasticsearch through spark jobs.
• Tech Stack - Dropwizard, Kafka, Elasticsearch, Apache Spark, MySQL, Java 8, Maven, Junit, Git, Jenkins
• · Reporting and Alerting: Build reporting, monitoring, and metrics of production deployed systems. For metrics cosmos, for alerts and monitoring Nagios and for reports Azkaban and crons jobs was used. This smoothened on-call process and quick resolution for any production issues.
• Tech Stack - Grafana, InfluxDB, Cosmos, Nagios, Azkaban, Cron (Linux)

Mar 2014 – Aug 2016 · 2 yrs 5 mos · Bengaluru, Karnataka, India

• As a part of the Customer Experience Platform team, I worked on -
• · Customer's Return Rule Engine - Build customer's return/refund/replacement policy engine of Flipkart.com from scratch. This was done by loading all business rules when the application boots up and dynamic change of business was also supported. All customer's returns/refund/replacement request is served by using this rule engine handling load of 4000 requests per second(RPS).
• Tech Stack - Dropwizard, Java Rule Engine(Drools), MySQL, Redis, Java 8, Maven, Junit, Git, Jenkins
• · Third Party Integration - Integrated external third party (outside Flipkart ecosystem) APIs through SAML protocol with our existing web console used by Flipkart’s customer support executives. This resulted in a 30% increase in revenue (~approx. 30 Cr.) as most of the queries were solved by troubleshooting rather than creating refunds of orders placed by the customer.
• Tech Stack - Dropwizard, SAML, MySQL, Java 8, Maven, Junit, Git, Jenkins
• · Streamlining customer support console - Combined 8 different consoles used by customer support executives/agents in a single web-based console. This was done by integrating with internal services (such as Callback to customer, Alternate Delivery Model of Flipkart, Flipkart first subscription, creating customer’s return/refunds/replacements) with our new console.
• · Customer Support Resolution Tool - Enhanced web-console used by Flipkart’s customer care agents to take corresponding actions for solving customer queries on phone call leading to better customer experience.

Jun 2013 – Feb 2014 · 8 mos · Noida, Uttar Pradesh, India

• Build RESTful APIs for exposing customer's medical data to the business team by consuming customers medical history event through Kafka topic and supporting CRUD operations on SQL database by following industry scale agile Software Development Life Cycle
• Tech Stack - Springboot, MySQL, Gradle, Junit, Apache Kafka, Bash Scripting, Docker, Kubernetes, Git

Aug 2012 – Dec 2012 · 4 mos · India

• Teaching Assistant for maintaining one of the college website using LAMP server portal
• Link - https://uspmes.daiict.ac.in/uspmes/welcome_login.php

Apr 2011 – Jun 2011 · 2 mos · India

• Developed augmented Reality applications using Qualcomm’s SDK Qcar.
• Team Size - 2