I have worked in various roles on the platform and productivity team within Netflix. My current team owns change management campaigns for code upgrades across the developer organization. Technologies: Kotlin, Salesforce, CockroackDB, ElasticsearchFormer projects include:Artifact DistributionTechnologies: Various in-house tools, Kotlin, Golang, Spinnaker- Created an Artifactory cluster that integrated with our IAM and Authz tooling to enable sharing of artifacts with contractors.DocumentationTechnologies: Kibana, Python, Elasticsearch, GraphQL, Kotlin, Spinnaker- Adopted and maintained Netflix's in-house documentation service, a custom wrapper around mkdocs. - Wrote tooling to track whether docs were well-maintained, creating a "health score" for docs, then added the score to a graphQL endpoint to be displayed in docs owner dashboards. - Put the docs service's graphql endpoints on the org's distributed graph. - Automated upgrades from old to new versions of mkdocs and other dependencies- Wrote tooling to make it easier to delete deprecated docs.

As the Engineering Lead on Packer, I help plan the tool roadmap, choose what community requests to prioritize, and give guidance to other engineers and community members on feature implementation.Under my leadership, the Packer team: * Separated Packer's core/plugin architecture from a monorepo into separately maintained plugin repositiories to ease community contributions.* Created a thoroughly-documented SDK to help community members create their own plugins* Revived an integration test suite that had gone unused for years* Created the HCP Packer Registry for the HashiCorp Cloud Platform* Cut the average number of open community pull requests awaiting review from 90+ to under 15* Implemented an entire new configuration language for the tool while continuing to support the old one until a 2.0 release* Modernized our binary release pipeline from being a manual process run from a team member's laptop into a PR-triggered release in Circle CI.

As a maintainer of the Packer open source project, I work primarily in Golang. My job is unique in that I don't have a primary "stack"; I change my stack multiple times a day depending on what issue I'm focusing on, and constantly learn new technologies in order to extend and improve Packer. Name a public cloud or a major operating system, and I've probably used its API or worked on some aspect of how Packer relates to it. I've done everything from handling environment variables in elevated Powershell scripting, to building out our integration with Oracle's Classic Compute Cloud, to chasing down race conditions between byte buffers, to community management and issue triage for the project.

My team was responsible for Sauce's highly performant automated testing cloud, which runs hundreds of thousands of Appium and Selenium tests every day -- each one on a pristine virtual machine booted for that specific test. Technologies included async Python, Docker, Ansible, Packer, Redis, Haproxy, Grafana, and kvm/libvirt. More granular details:* Became the go-to engineer for difficult investigations of systemic issues: reduced specific internal error rates from 0.1% to 0.00%, and reduced VM start time under load by 2.5x * Led the project to automate the acquisition and installation of leading web browsers as they are released, dramatically reducing developer time and attention required to release the ever-changing offering of browsers.* Helped transition Sauce's OSX vm build and configuration process from a tedious manual effort with no documentation to a fully-automated continuous integration build using Packer and Ansible. * Helped transition Sauce's OSX offering from VMware to Libvirt.* Refactored legacy asynchronous Python code and cleared thousands of lines of technical debt* Implemented automatic safety pre-flight checks for our daily deploy process* Built dashboards to give insight into the overall health of our cloud (grafana)* Wrote monitoring tools using nagios and statistics from grafana* Provided technical leadership for our Desktop Platform Support scrum team* Onboarded new developers* Mentored junior developers through pairing and 1:1 meetings* Wrote extensive documentation to help new team members learn our processes, technologies, servers, etc.

* Manually maintained the vms used in our service, adding new platforms and browsers to the Sauce offering as they were released* Implemented customer-facing tools to allow specialized configuration of our vms, such as the ability to set specific vm screen resolution* Investigated and fixed customer-reported bugs* Wrote tools to leverage vSphere's API, allowing for efficient distribution, maintenance, and deletion of VMWare VMs throughout our cloud.

- Supported and developed in-house matlab-based image processing software for use by researchers- Wrote features to display and segment regions of interest, measure joint space width, batch process files, and perform statistics for voxel-based morphology analysis of knee atlases- refactored legacy code with emphasis on testability and DRYness- Migrated existing research data from Sybase to REDCap MySQL system, and automatically parsed information from an XML feed updated daily with new patient surveys and information for insertion into new database- Wrote the software tool for joint-space-width analysis of data, performed data analysis, and wrote manuscript for a study examining the effect of weight-bearing on MRIs of knee cartilage by using a pulley system to apply axial load to patients’ feet, simulating standing while lying in MRI bed

Performed research under direction of Dr. Jill McNitt-Gray on the biomechanics of NCAA Division I female volleyball players.Analyzed data from a case study of a Taiko drummer. Performed experimental design. Collected and analyzed video, force plate, and EMG data. Digitized videos to obtain kinematic information about movements, created video overlays using Dartfish, and processed EMG data using Matlab.