Software Engineer @ Databricks | Kubernetes Autoscaling | University of Waterloo, BCS
Software Engineer with experience building large-scale, cloud-native infrastructure.
Member of the Kubernetes Autoscaling team at Databricks, working on systems that improve efficiency, reliability, and scalability of large-scale data workloads. Primary focus is Autopilot, an intelligent autoscaler that leverages historical workload patterns to dynamically adjust CPU and memory resources.
Key areas of contribution include:
Efficiency optimization through intelligent VM instance selection and management
Cluster health monitoring to ensure stability, scalability, and cost-effectiveness at massive scale
Enhancements that enable Databricks customers to run data and AI workloads seamlessly and efficiently
Dedicated to building cloud-native infrastructure that balances performance, reliability, and cost savings for enterprise-scale data platforms.
Implemented log parser in Python to parse trade logs into KDB database, using Q to query the database and calculate stats such as fill % and return results to the user interface
•
Built an analytic dashboard in React to show linkage through trade process from client to market, allowing traders to easily query client orders and discover where slippage was occurring
•
Collaborated closely with traders to gather user feedback and requirements, translating their input into a user interface
Ported over a rules service engine to follow new language specifications, allowing new detections to be run for a user behavior threat detection software
•
Used Java to write and JUnit test new compiler functionality, with over 92% code coverage
•
Added support for JSON structures and implemented optimizations to flatten AST involving nested field extractions
Implemented interface and functionality using TypeScript with React for user account and influencer pages for an e-commerce website
Developed scripts using GraphQL to query and mutate data as well as storing and updating the cache directly, leading to a 40% reduction in network traffic
Implemented Google Analytics tracking throughout the site to track user interaction as well as API calls
