Veena Basavaraj is a seasoned engineering leader with 14+ years building and scaling consumer and enterprise systems, currently heading Apps Platform at Benchling after leading 200+ engineering and data teams across WeWork’s global org. She combines product-minded execution—driving booking, commerce, and physical access systems—with deep platform expertise across frontend, backend, data pipelines, streaming, and ML infrastructure. Past roles include building Einstein.AI’s deep learning platform after the Metamind acquisition and leading Uber’s data streaming platform, plus staff-engineer work at LinkedIn that helped scale services from 60M to 350M users. Veena is hands-on with open source maintenance experience (notably contributing to Dust.js improvements) and routinely blends global strategy with local execution tradeoffs. She is known for developing talent and aligning engineering roadmaps to measurable business KPIs in high-impact, cross-functional environments. Based in San Francisco with an MS in Computer Science from Virginia Tech, she thrives on turning complex data and ML capabilities into reliable product experiences.
14 years of coding experience
19 years of employment as a software developer
M.S. Computer Science, M.S. Computer Science at Virginia Tech
Asynchronous Javascript templating for the browser and server
Role in this project:
Full-stack Developer
Contributions:209 commits in 1 year 8 months
Contributions summary:Veena primarily focused on maintaining and updating the Dust.js templating library. Their contributions involved cleaning up helper functions, adding features like loop index and length markers, and updating documentation. The user also fixed formatting issues and updated test names and descriptions, indicating a focus on code quality and usability. Furthermore, they made fixes related to the parsing and evaluation of Dust templates.
Contributions:2 commits, 8 pushes, 1 branch in 1 day
apachesqoopsparkscalaapache-spark
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