Deepak Bansal
Software Engineer at Alchemy
Austin, Texas Metropolitan Area United States
Summary
🤩
Rockstar🎓
Top SchoolDeepak Bansal is a seasoned software engineer with 7 years of professional experience based in the Austin, Texas area, currently contributing to Alchemy after a long tenure at Microsoft. He specializes in back-end development and data transformation, demonstrated by contributions to the widely used microsoft/FHIR-Converter project where he implemented Handlebars helpers, improved resource templates, and resolved parsing and formatting errors. Deepak blends production-grade maintenance—upgrading npm packages, separating test data, and fixing documentation—with feature work that improves conversion accuracy for healthcare interoperability. His background includes hands-on engineering roles dating back to early-career work at Quark Media House and technical leadership experience at Microsoft, reflecting depth across enterprise-scale systems. Collected training from Delhi College of Engineering underpins a pragmatic approach to solving complex integration challenges. Colleagues describe him as detail-oriented and quietly impactful, often tackling the fiddly data issues that make large systems reliable.
7 years of coding experience
18 years of employment as a software developer
Bachelor of Engg, Bachelor of Engg at Delhi College of Engineering
Github Skills (8)
smart-on-fhir10
hl7-fhir10
handlebars10
converter10
template-engine9
javascript9
templater9
template-tags9
Programming languages (4)
Github contributions (5)
microsoft/FHIR-Converter
Feb 2020 - Jul 2020
Conversion utility to translate legacy data formats into FHIR
Role in this project:
Back-end Developer
Back-end DeveloperContributions:2 releases, 72 commits, 17 PRs in 4 months
Contributions summary:Deepak primarily contributed to the development and maintenance of the FHIR converter utility. Their work includes implementing Handlebars helpers, which are core components of the conversion process. They upgraded npm packages, separated messages, and test data, along with fixing documentation and improving resource templates. Additionally, the user worked on fixing errors related to parsing and formatting, indicating a focus on data transformation and improving the accuracy of the conversions.
hl7v2openxmlfhirdata-formatsfhir-converter
deepak-ms/DLWorkspace
Apr 2019 - Jul 2019
Deep Learning Workspace
Contributions:38 pushes, 10 branches in 3 months
caffe2deep-learningworkspaceneural-networksmachine-learning
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