Cloud-Native Platform Engineer developing for Cloud-Native Data Processing, with Kubernetes and Spark. Development in Go and Python. Infrastructure supporting machine learning, model generation, inference, LLMs, etc.
Hyper-growth cybersecurity startup backed by Sequoia Capital & Y Combinator, with at least a dozen clients you recognize by name. (And likely many more.) š
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Sample project: rebuilt client notifications platform and architecture to be cloud-native, including a new Slack app; focus on adaptable design for present and future cloud-based, multi-channel distribution
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Customer adoption & engagement of Slack app exceeded expectations by more than 1000%; customer satisfaction greatly exceeded expectations
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Full-stack; software design; cloud architecture; engineering; testing; software development life cycle (SDLC); agile methodologies
Ads Measurement team: collect & analyze billions of events per day to measure impact of ads across dozens of metrics on high availability systems
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Designed and implemented multi-team changes to on-/offline data collection & analysis pipelines to expand pin visibility & conversion performance contributing to 6x increase in number of businesses placing ads with Pinterest Q4 2020 (outlined in shareholder letter below)
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Led development of framework for analysis of server deployments with automatic failsafes to reduce rollout friction, enabling at-a-glance checks, saving > 10 hours of engineer time per week
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Ownership of Pinterest advertising tag, including leading adoption of modern JavaScript coding standards and automatic integration testing and rollout analysis, saving > 15 hours of engineer time per rollout and reducing time to deploy from multiple days to < 1 hour
