Varun Panigrahy

Software Engineer

Sunnyvale, California, United States3 yrs 1 mo experience

AI EnabledAI ML Practitioner

Key Highlights

Expert in optimizing distributed systems for cloud performance.
Proven track record in enhancing data processing infrastructure.
Strong background in healthcare technology solutions.

Stackforce AI infers this person is a Backend-heavy Fullstack Engineer with expertise in Infrastructure and Cloud Technologies.

Contact

Skills

Core Skills

Distributed SystemsNode.jsAlgorithms

Other Skills

Operating SystemsDatabasesJavaHadoopMicrosoft AzureSpring BootAmazon Web Services (AWS)Low-Level DesignData ScienceNeural NetworksNatural Language Processing (NLP)Computer VisionMachine LearningArtificial Intelligence (AI)Apache Spark

About

I’m a Computer Science graduate student at the University of Massachusetts Amherst (M.S., ’25), passionate about distributed systems, infrastructure engineering, and cloud-scale performance optimization. Previously, I worked as a Software Engineer at Microsoft on the Azure Spark Runtime team, where I built and optimized large-scale distributed infrastructure powering data processing for global enterprises. My work focused on improving Spark-SQL’s query optimizer, adaptive execution, and runtime reliability for multi-billion-row workloads. At Juniper Networks, I optimized the Junos EVO OS object monitoring subsystem, redesigning shared-memory structures to cut CPU utilization by 25% under high load

Experience

3 yrs 1 mo

Total Experience

1 yr 5 mos

Average Tenure

3 mos

Current Experience

Google

Software Engineer III

Feb 2026 – Present · 3 mos · Sunnyvale, California, United States · On-site

Juniper networks

Software Engineering Intern

Jun 2025 – Aug 2025 · 2 mos · Sunnyvale, California, United States · On-site

Optimizing Objmon CPU Utilization: Optimized Objmon, the Junos EVO (The Distributed OS which runs on juniper routers) object monitoring daemon, by eliminating costly deserialization and re-serialization cycles of millions of objects transmitted via shared memory; redesigned payload structure to embed shared segment length and offset, enabling direct byte-wise access and reducing inter-process communication overhead. Reduced CPU Utilization by 25% during high churn time.

Distributed SystemsOperating Systems

Philips

Software Engineer Co-op

Feb 2025 – Jun 2025 · 4 mos · Cambridge, Massachusetts, United States

SDE Co-op in the Clinical Insights and AI team. Worked on creating next generation hospital patient monitoring systems and clinical insights solutions using Spring Boot, SQL, .net, Bash Scripts, Java and AWS. Contributed to Clinical Insights Manager transforming historical patient data into actionable insights to help healthcare teams evaluate clinical events and optimize performance.

Node.jsDatabases

Microsoft

2 roles

Software Engineer

Jul 2021 – Jan 2024 · 2 yrs 6 mos · Bengaluru, Karnataka, India

Engineered catalyst optimizer enhancements, drove Adaptive Query Execution (AQE) advancements, and refined Referential Integrity (RI) for Spark-SQL. Pioneered the development of the Autoupgrade tool using Java and Python, then seamlessly deployed it on an AzureDevOps pipeline to accelerate the release process of Spark Virtual Hard Disks (VHD). Managed the migration of Spark Virtual Hard Disks from Ubuntu to Mariner.

JavaDistributed Systems

Software Engineer Intern

May 2020 – Jul 2020 · 2 mos · Hyderabad, Telangana

Developed and implemented a High Availability solution for Yarn Resource Manager, leveraging Raft protocol in Java; eliminated standby RM failover delays caused by Apache Zookeeper, ensuring seamless operations and faster recovery times

AlgorithmsHadoop