Alper Silistre

Cloud Solution Architect at Portera

Alper Silistre is a skilled Cloud Solution Architect at Portera since January 2020, leading cloud-based software projects for international clients and applying technical expertise to develop effective solutions. Previously worked as a Cloud Engineer, managing the cloud platform for a multi-national client, where responsibilities included configuring Infrastructure as Code, automating management jobs, and ensuring adherence to governance standards. Alper's background includes experience as a Software Engineer at broadAngle, focusing on full-stack development with Microsoft technologies, as well as contributions to game development and an accounting program during internships. Alper holds a Master of Computer Science from Ege University and a Bachelor of Science in Computer Software Engineering from Izmir University of Economics.

Location

Amsterdam, Netherlands

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Portera

Portera orchestrates technology to help out businesses to structure and develop total digital strategy that can deliver against business objectives. Our main goal is to convert technology to a commercial driver by leveraging state of the art technology to enable data driven decision making. Our digital business design experts can help assess, strategize and prototype new digital models by working with technology consultants to directly answer to the desired experience for internal users and consumers. Unlike most technology providers, we have successfully embedded the bi-modal IT structure where we can deliver end to end technology solutions with the 2-speed IT process which enables us to both deliver small mobile apps and large scale integrations. Our mixed approach to agile, provides flexibility on the requirements level and visibility on the executive level. We also help organisations by running their Program Management Office, to bring efficiency and reliability on the technology solutions that they’ve invested. We run data mining hubs within our organisation that reports directly to our clients to let them capitalize on their existing data and explore future opportunities on real-time trajectory prediction together.