Over 20 years of software development and enterprise architecture experience with large companies such as Microsoft, Toyota, Honeywell, BrightView, Intel, K2 and Washington Mutual. Skilled in all areas of software development and delivery cycles including architecture, business analysis, client training and production support. Extensive experience in managing multiple and conflicting software development projects under aggressive timelines.
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Azure Search – indexed company data (vehicles, heavy equipment,
assets, employees, jobs, sites, material orders, safety inspections
documents, etc.) that can provide personalized and relevant
results, based on who you are, where you are and what you do in
the application
Azure App Service (Web) / Azure Function App (API) - powerful
PaaS (Platform-As-A-Service) that allows for the automatic scale up
and out, based on the current user load. Combination of serverless
and hosted instances.
Azure SQL – powerful PaaS (Platform-As-A-Service) that allows for
the automatic scale up and out, based on the current user load.
Implemented cross data center replication with read only replica to
isolate the transactional system from the data analytics one
Power BI / Azure Analysis Services – powerful business
intelligence tool that allows for the creation of data visualizations
once and their use for multiple purposes later: business intelligence
and application interaction / what-if analysis
Form Engine – implemented basic form engine framework that
allows for the creation of forms in declarative way for
rapid development (low code). This enabled the generalization of email/text message notifications, PDF generation, OCR and data analytics components. Implemented document scanner capability throughTensorFlow that ensures that the captured image is in focus and
readable. Used Azure Computer Vision as OCR tool in order to
digitize documents that were captured through the application
Docker Containers
- PDF generation with Chromium in Azure, since the standard
Function API is running in isolated mode
- IoT Edge module that allows the telematics devices, installed on
the vehicles / heavy equipment to connect to Azure via TCP.
Implemented in Java and hosted on multiple Linux servers, with
a load split, based on the latency from the device to the server
Azure Streaming Analytics – implemented module that allows the
analysis of the telematics data in real time and the detection of
speeding, asset theft, geo-fence events (defined in the application),
data archiving, etc.
Azure Data Factory – implemented different data integration
pipelines that bring required data from various on-premises and/or
cloud system in Azure SQL / Azure Storage
Azure DevOps – implemented build and deployment pipelines for
the Angular application and the API that rely on the Git repository
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AR Motorcycle Racing - real time data and video streaming within a virtual reality
they are looking at the real motorcycle.