Siddhant Sorann
Software Engineer at Rubrik
Sunnyvale, California, United States
Summary
👤
Senior🎓
Top SchoolSiddhant Sorann is a results-driven software engineer based in Sunnyvale with a decade of industry experience and a 4.0 MS in Computer Science. He has a strong track record of shrinking system latencies and costs—most notably cutting a programmatic Ad-Tech pipeline from 60 minutes to 45 seconds and improving API latency by over 90%—while leading cross-functional teams and championing TDD and DevOps practices. Skilled across Java, Python, Ruby, Kubernetes, and cloud platforms, he has driven search-performance gains at MathWorks (42% faster service, 38% better relevance) and contributed backend fixes and filters to the Spring Cloud Dataflow project. Comfortable shipping full-stack and distributed systems, Siddhant blends hands-on coding with operational telemetry (Prometheus/Grafana) to deliver reliable, scalable products. He’s now applying that mix of performance-first engineering and cloud-native expertise to ambitious software challenges in the Bay Area.
9 years of coding experience
4 years of employment as a software developer
Master's degree, Computer Science, 4.0/4.0, Master's degree, Computer Science, 4.0/4.0 at Arizona State UniversityBachelor of Technology (B.Tech.), Computer Science, Bachelor of Technology (B.Tech.), Computer Science at Vellore Institute of Technology
English, Hindi
Stackoverflow
313reputation
30kreached
3answers
21questions
Github Skills (22)
api-rest10
api-design10
restful-api10
java10
javas10
spring-boot10
rest-api10
batch-processing10
data-pipelines9
microarchitecture9
micro9
data-pipeline9
stream-processing9
microservices9
hibernate6
Programming languages (4)
Github contributions (5)
spring-cloud/spring-cloud-dataflow
Aug 2020 - Feb 2021
A microservices-based Streaming and Batch data processing in Cloud Foundry and Kubernetes
Role in this project:
Back-end Developer
Back-end DeveloperContributions:19 reviews, 8 commits, 20 PRs in 6 months
Contributions summary:Siddhant primarily contributed to the back-end functionality of the Spring Cloud Dataflow project. Their commits focused on validating application names within the AppRegistry, adding date range filtering for job executions, and implementing a filter for task definitions. They also made improvements to the existing codebase, fixed issues, and added test cases. These changes suggest a focus on enhancing core features and improving data processing capabilities.
stream-processingfoundrydatapipelinesbatch-processingorchestration
miqdigital/spring-cloud-dataflow
Aug 2020 - Mar 2021
A microservices-based Streaming and Batch data processing in Cloud Foundry and Kubernetes
Contributions:6 reviews, 30 PRs, 42 pushes in 6 months
foundrybatchdata-processingcloud-foundrystreaming
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