# Shubham Mehta > Software Engineer (Systems & OS) | OneFS / FreeBSD | Cloud Storage & Platform Feature Development | C / Python Location: Boston, Massachusetts, United States Profile: https://flows.cv/shubhammehta I am a systems- and OS-focused software engineer building storage and platform features across cloud-integrated environments and on-prem scale-out systems. At Dell Technologies, I work on OneFS across multiple deployment models, including OneFS Image on AWS & Azure, PowerScale hardware, and Dis-aggregated storage. My work spans OS-adjacent storage subsystems, platform APIs, and infrastructure for cloud and on-prem deployments, including drive subsystem enhancements, pre-boot configuration workflows, and orchestration services that translate customer requirements into scalable cluster deployments. In parallel, I have contributed to PowerScale disaggregated storage, focusing on configuration and connectivity for NVMe-oF architectures. This includes configuring userspace libraries and kernel parameters to establish and manage TCP and RDMA connections to NVMe-oF subsystems for reliable, high-performance communication on a FreeBSD based OS. I identify workflow inefficiencies and proactively build targeted automation to eliminate them - test infrastructure, and Python tooling that streamline deployments, improve pre-merge signal quality, and boost developer productivity. I also apply Infrastructure-as-Code practices, including Terraform, to evolve and maintain infrastructure through reviewable, version-controlled changes. Beyond systems development, I have applied these platforms to data-heavy and ML-driven workloads: building ingestion pipelines and databases, developing pattern-recognition and analytics automation, and working with NLP and computer-vision workflows (clustering, classification, and object detection) in data-intensive environments. I have delivered measurable impact in production systems, including reducing customer deployment time by 35%, I improved pre-merge test reporting visibility across 30+ teams . Previously, I worked in performance engineering, designing experiments and automation to evaluate and optimize scale-out storage systems across configurations. I enjoy working close to the platform layer on performance-critical, reliability-focused systems and am drawn to roles where systems insight, automation, and applied data work improve product quality and developer efficiency. ## Work Experience ### Software Engineer II @ Dell Technologies Jan 2023 – Present | Boston, Massachusetts, United States ### Software Engineer @ Dell Technologies Jan 2021 – Jan 2023 | Boston, Massachusetts, United States • Part of the performance engineering team that analyzes and optimizes the performance of Dell’s enterprise storage product (PowerMax). • Designed and executed experiments to assess the performance of the PowerMax storage array. • Developed a bash script that centrally applies changes to crontabs on all servers in the lab and can fetch/push data from all servers. • Modified our automated performance gauge script to a generic script that was compatible with all 6 configurations of PowerMax. • Designed and managed PDC automation dashboard to generate performance graphs with latest available data and streamlined automation to improve data generation by 43.3% ### Software Engineer @ Quiver Quantitative Jan 2020 – Jan 2021 • Developed a Python script to perform sentiment analysis using Text2emotion library on Reddit’s Wallstreetbets dataset for any selected stock ticker and time range. • Developed a Python dashboard to visualize sentiment analysis data using line graph and pie chart for a selected ticker and time range. • Developed an automated TikTok scraper API that routinely collects latest feed data from verified users and users that frequently post financial data and stores it on a PostgreSQL database. Cumulatively collected 5+ million rows of user data in 2 months. ### Secretary @ Google Developers Jan 2020 – Jan 2021 | Madison, Wisconsin, United States ### Peer Mentor~Comp Sci 537 (Introduction to Operating Systems) @ University of Wisconsin-Madison Jan 2020 – Jan 2021 | Madison, Wisconsin, United States • Hosted office hours and addressed students' questions about the course content and Operating systems programming projects. • Helped students debug their projects in C. • Worked under Prof. Andrea C. Arpaci-Dusseau in 2020. • Worked under Prof. Barton Miller in 2021 ### Peer Leader ~ Java Data Structures (WES CS 300) @ University of Wisconsin-Madison Jan 2019 – Jan 2021 | Madison, Wisconsin, United States • Hosted weekly classes to go over instructor-designed interactive Java programming assignments. • Helped with designing interactive learning activities for Java. • Worked under Prof. Tracy Lewis-Williams and Amanda Captain ### Peer Mentor ~Comp Sci 577 (Design and Analysis of Algorithms) @ University of Wisconsin-Madison Jan 2020 – Jan 2020 | Madison, Wisconsin, United States • Hosted regular office hours to help students with course content and provide assistance for their weekly homework. • Worked under Prof. Jin-Yi Cai. ### Software Engineer Intern @ Dell Technologies Jan 2020 – Jan 2020 | Seattle, Washington, United States • Designed data storage, data collection, and data analysis standards to improve the quality of data retrieved from multiple Dell products and solutions to make it Machine Learning algorithm friendly. • Built Alteryx workflows to identify missing critical events/information in multiple databases with a total data size of 800+ GB. • Developed SQL queries and python scripts in Alteryx to detect multiple event patterns which collectively results in generating 16% of the Service Requests. • Developed a python script to pre-process the data and implemented Unsupervised-Text-Clustering using NLP. • Leveraged TensorBoard to visualize the clusters in 3-D to evaluate its compatibility with Machine Learning algorithms. • Improved the clustering by 72% through applying the standards recommended by us to the dataset. ### Perception team - Autonomous F1 Car @ Wisconsin Autonomous Jan 2018 – Jan 2020 | Madison, Wisconsin Area • Developed a Python script to process the raw point-cloud data retrieved from SICK lidar and visualized it through the SOPAS Engineering tool. • The derived point cloud data is fed into ROS, to evaluate the image of the object and contribute to path-planning. • Processed the .bag file of the extracted images of the cones through YOLOv3 object recognition algorithm by integrating it with the ROS framework. ### Software Engineer Intern @ naviHealth Jan 2019 – Jan 2019 | Boston, Massachusetts • Programmed a data governance application, using .NET and C#, to routinely synchronize subscribed users between the organization’s Oracle Data Warehouse and Tableau’s PostgreSQL Database. • Built a Trusted Authentication console application, to impersonate subscribed users and retrieve a snapshot of the client’s dashboard for the support team. Improved support team’s SEV-1 resolution capacity by 15%. • Designed a C# API library with user authentication capability to access and edit NaviHealth’s Tableau interface through PowerShell. • Developed test cases using SQL and Apache Groovy in ICEDQ to automate testing and regulate data warehouse quality. ## Education ### Master of Science - MS in Data Science (In Progress) The University of Texas at Austin ### Bachelor of Science - BS in Computer and Information Sciences, General University of Wisconsin-Madison ### Boston University ### High School Diploma Shardayatan School ## Contact & Social - LinkedIn: https://linkedin.com/in/shubham-mehta58 --- Source: https://flows.cv/shubhammehta JSON Resume: https://flows.cv/shubhammehta/resume.json Last updated: 2026-03-31