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Parth Nagarkar

Software Engineer

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About Me

A Software Engineer at Amazon Web Services (AWS) with an MS in Computer Science from Stony Brook University. Specializing in backend development, I'm currently a part of the AWS Supply Chain product team, focusing on the Demand Forecasting module. My hands-on experience ranges from architecting scalable systems to collaborating with diverse teams to ensure efficient data processes. I bring expertise in multiple programming languages and frameworks, including Python, Java, Spring, Flask, and AWS. My stint at Amazon has fortified my knowledge in supply chain systems, and I take pride in influencing architectural decisions and upholding AWS standards.

Experience

Amazon Global Logistics

Software Development Engineer

  • Designed and implemented a ship option management system for dedicated contracted carrier capacity, authoring Low-Level Design documents and building APIs with complex scheduling logic across multiple appointment scenarios — directly addressing high load rejection rates and rising transportation costs.
  • Architected external service integration infrastructure using CloudAuth and AWS PrivateLink, establishing secure cross-VPC connectivity patterns with comprehensive retry policies and fault-tolerant error handling.
  • Led end-to-end migration of enterprise data pipelines across AWS regions under a compliance mandate, discovering a critical architectural constraint in S3 event notifications and pivoting the migration strategy — delivered with zero service disruption.
  • Implemented cross-region data replication using DynamoDB Streams and Kinesis, building comprehensive cloud infrastructure including CloudFormation templates, IAM policies, KMS encryption, and EventBridge configurations.
  • Owned a workstream in a legacy-to-modern service architecture migration, modernizing dependency injection frameworks, reducing Lambda deployment package size by 21%, and coordinating multi-region production deployments.
  • Resolved critical production issues post-launch including complex state synchronization bugs, and achieved 83% reduction in recurring operational alarms through systematic root cause analysis and infrastructure optimization.• Designed and implemented a ship option management system for dedicat
  • Technologies: Kotlin, Java, Python, TypeScript, AWS

Amazon Web Services

Software Development Engineer

  • Engineered synchronous data query APIs for an enterprise demand planning application, replacing asynchronous batch export jobs and reducing data access latency from 20+ seconds to under 6 seconds — a 4x improvement for customers.
  • Built a data processing pipeline enabling customers to ingest supplementary time series data for ML-based demand forecasting, implementing comprehensive validation, transformation logic, and production monitoring with automated alerting.
  • Delivered a full-stack file upload system for forecast overrides spanning React, GraphQL, and Kotlin — implementing ~20 validation checks, row-level error reporting, dynamic template generation, and cloud-based file storage.
  • Led the design review for a GraphQL API schema serving as the middleware between frontend and backend services, collaborating across teams to ensure optimal contract design.
  • Executed load testing and capacity planning for production APIs, analyzing system performance under various conditions and configuring service limits for scalability.
  • Root-caused and resolved a customer-impacting high-severity incident that was reviewed as a Correction of Error, owning end-to-end resolution from diagnosis through emergency production deployment.
  • Created operational runbooks, updated team documentation, and authored a coding best practices guide adopted by the team.
  • Technologies: Kotlin, Java, TypeScript, AWS

Jefferson Health

Software Developer

  • Spearheaded the resolution of 30+ critical bugs in MINRbase, a comprehensive database of nuclear- and mitochondrial-ribosomal-RNA-derived fragments (rRFs) using J2EE, JSP, and jQuery, facilitating its publication in the Nucleic Acids Research journal.
  • Focused on optimizing software development components of MINRbase, enhancing functionality and user engagement.
  • Executed a successful migration of the LicensePlates tool to Django, ensuring efficient RNA sequence analysis and dataset identification.
  • Contributed to the identification and classification of RNA sequences in LicensePlates, aiding in the recognition of miRNA/isomiR, tRF, and rRF.
  • Technologies: Java, Python, SQL, jQuery

Amazon Supply Chain

Software Engineering Intern

  • Built a service to compare the buying plans for inventory procurement generated by legacy system and new system to validate the performance of the new system before release to production.
  • Implemented a design to set up Amazon SQS and transfer generated plans from the two systems to comparison API.
  • Engineered an API design to receive the generated plan data, parse it and store the data Amazon DynamoDB table.
  • Incorporated JUnit and Mockito unit testing frameworks to achieve line coverage of 95% and branch coverage of 98%.
  • Developed the comparison logic to compare the plans and send them to ElasticSearch for visualizing it using Kibana.
  • Technologies: Java, Spring, TypeScript, NoSQL, Amazon DynamoDB, Amazon SQS, Amazon OpenSearch, Elastic Stack

Stony Brook University

Research Assistant

Stony Brook University

Graduate Teaching Assistant

  • Working as a teaching assistant for an undergraduate course named Cloud Computing (ISE-390) having 100 students.
  • Executing all teaching assistant duties including mentoring, lecturing, researching and clerical help.

Stony Brook University

Graduate Teaching Assistant

  • Working as a teaching assistant for an undergraduate course named Fundamentals of IT (ISE-218) having 150 students.
  • Executed all teaching assistant duties including mentoring, lecturing, researching and clerical help.

Hiranandani Group of Companies

Data Science Intern

  • Implemented web scraping module of a project to extract Twitter data to identify and connect with potential real estate buyers.
  • Engineered Python scripts to scrape data from Twitter using Twitter API, BeautifulSoup and clean the data using NLTK.
  • Designed a multi-staged method for data extraction, ranking the prospective buyers and scraping their contact information.
  • Leveraged multithreading and parallel processing using tools like Google Colab to optimize execution time by 40%.
  • Technologies: Python, SQL, Twitter API, Pandas, Numpy, NLTK, Google Colab, BeautifulSoup, REST APIs.

TryCatch Group

Machine Learning Intern

  • Developed a URL classification system using Python for scraping data to classify URLs as benevolent or malicious.
  • Performed preprocessing and feature engineering using Numpy, Pandas and trained machine learning models using Sklearn.
  • Built web crawler to scrape URLs from a website using BeautifulSoup and deployed it on AWS by using Flask in backend.
  • Enhanced feature generation performance by implementing caching and multiprocessing to speedup execution by 30%.
  • Technologies: Python, AWS, Flask, Numpy, Pandas, BeautifulSoup, Sklearn, NLTK.

Larsen & Toubro Infotech

Software Engineering Intern

  • Worked in an Agile team of .NET developers and designed an Ecommerce website for Handicraft products.
  • Implemented a live visit counter to count the number of daily unique visitors on the website using HttpCookie.
  • Technologies: ASP.NET, HTML5, CSS3, jQuery, Bootstrap, MS SQL Server.

Education

Stony Brook University

August 2021 - December 2022

Masters in Computer Science

Coursework: Theory of Database Systems, Artificial Intelligence, Data Science Fundamentals, Computer Vision, Smart Energy in the Information Age.

University of Mumbai

August 2018 - July 2021

Bachelor of Engineering in Computer Engineering

Thakur Polytechnic

August 2015 - July 2018

Diploma in Computer Engineering

Publications

MINRbase: a comprehensive database of nuclear- and mitochondrial-ribosomal-RNA-derived fragments (rRFs)

October 2023

Nucleic Acids Research

As a software engineer on the MINRbase launch, I helped enhance and harden an interactive web database that lets researchers explore 130,238 human nuclear- and mitochondrial-rRNA–derived fragments (rRFs) mined from 11,632 public datasets (including GEUVADIS and TCGA).  The platform supports complex, metadata-driven queries (e.g., sequence, parent rRNA, abundance thresholds, tissue/disease) and delivers interactive visualizations (implemented with Highcharts) so users can quickly filter, inspect, and plot rRF expression profiles at scale. 

Paper Link

Social Media Intelligence for Brand Analysis

July 2021

IEEE International Conference On Computing, Communication and Networking Technologies (ICCCNT)

This paper aims to provide a real-time solution to stream the tweets from Twitter related to a specific brand and analyse them in real-time in order to extract insights from the tweet data that allows the brands to know what exactly are the social media users’ perceptions about them.

Paper Link

Code

Twitter Data Mining for Targeted Marketing

July 2020

IEEE International Conference on Inventive Research in Computing Applications (ICIRCA)

This paper aims to provide an approach to target users on Twitter by discerning their preferences with the use of unique keywords in the real estate sector.

Paper Link

Security System Based on Sclera Recognition

February 2018

International Research Journal of Engineering & Technology

The vessel patterns of Sclera are unique for each individual. Considering this uniqueness, a biometric system was developed to authenticate users based on their Sclera. This system captures a photo of the user's eye and preprocesses the image to extract vessel patterns. Further, the extracted vessel patterns are matched with the existing users' vessel patterns from the database to authenticate the user.

Paper Link

Code

Projects

Socialis

Developed a real-time social media intelligence tool to stream tweets from Twitter pertaining to a specific brand that performs various types of analyses based on the textual and location data and plots the insights graphically on a dashboard in real-time to enable the brand to better understand their audience with intelligent insights.

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Twitter Profile Analyzer

Developed a Twitter analytics application that extracts rich insights from any public Twitter profile. Retrieved and analyzed data about tweets, likes, followers and location. Implemented techniques like sentiment analysis, named entity recognition and so on.

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Security System Based on Sclera Recognition

The vessel patterns of Sclera are unique for each individual. Considering this uniqueness, a biometric system was developed to authenticate users based on their Sclera. This system captures a photo of the user's eye and preprocesses the image to extract vessel patterns. Further, the extracted vessel patterns are matched with the existing users' vessel patterns from the database to authenticate the user.

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LinkedIn Followers Bot

Designed a Bot using Selenium to send connection requests in bulk to recommended profiles. Added a delay of 3-7 seconds to avoid getting detected by LinkedIn.

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Blog Website

Launched an online blog website that allows users to create, update and delete posts. Implemented features such as user authentication session management, cloud image uploading and email verification.

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Twitter Data Mining for Targeted Marketing

Engineered scripts to scrape data from Twitter about tweets, user profiles and location to target users on Twitter by discerning their preferences with the use of unique keywords in the real estate sector.

View Project

Skills and Technologies

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