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Software Engineer Resume

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Taylor, MI

TECHNICAL SKILLS

  • Jenkins
  • OpenShift/Kubernetes
  • Docker
  • Concourse
  • Agile
  • Linux
  • Android Studio
  • Git
  • Python
  • Java
  • Bash Shell Scripting
  • Azure

PROFESSIONAL EXPERIENCE

Confidential, Taylor, MI

Software Engineer

Responsibilities:

  • Developed and maintained pipelines for continuous integration/delivery of FordPass/LincolnWay applications
  • Automated various processes that have led to a significant increase in productivity and efficiency for the DevOps Team, among them:
  • Wrote a Python script that automated the entire compliance audit process for all microservice and mobile app teams
  • Original manual process took upwards of 60 hours to complete, and needed to be performed several times per year and was error - prone and had many gaps
  • New automated process runs as an intermediate job on the pipelines with each check taking seconds instead of hours
  • Process is proactive instead of reactive leading to elimination of noncompliance within the organization
  • Docker image update for all regions/applications
  • Wrote a shell script that runs on a time resource-triggered pipeline that automatically updates our docker image with the latest dependencies being used in the codebase
  • A four hour weekly manual task was optimized to become a one hour daily automated task, saving approximately 200 hours of manual effort per year and improving efficiency and efficacy of the existing process
  • This eliminated timeout issues on our build pipelines that resulted from trying to download the dependencies at runtime
  • Automated the entire release branch cut and pipeline deployment process
  • Release branch cut, Slack announcements, deployment of release pipelines and incrementing of master branch version number all now run at the click of a single button, and can even be scheduled to run automatically by creating an event on the calendar

Confidential, Dearborn, MI

Android Developer

Responsibilities:

  • Part of a two-person development team working on a project in conjunction with Ford
  • Developed a multi-modal sensor array application
  • Streams data in real time from four different sensors
  • ECG, Smart Watch, Ambient Temperature, and Smart Thermostat
  • Data is streamed to a server-based incremental machine learning model
  • Model adapts and will adjust the user’s environment based on sensor input and user preferences to maximize comfort in real time
  • Application was built from the ground up
  • Involved the integration of 4 different sensors from 4 different companies
  • Implementations included JSON, REST, multithreading, OAuth, Bluetooth

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