Do you thrive on automating workflows and optimizing cloud architectures? At PVision, we are looking for a skilled Cloud Automation Engineer to streamline business processes and enhance our AWS-based operations. Be part of a team dedicated to improving efficiency and delivering scalable, reliable solutions to empower green energy. We are looking for in intern for 6 month, starting between january and march.
Tasks
* Automate manual workflows, such as filling Word documents based on Excel data.
* Develop and optimize integrations between various AWS services (e.g., S3, RDS, Lambda).
* Design, implement, and maintain serverless architectures to support end-to-end processes.
* Create scripts and automation solutions to improve efficiency and reduce manual interventions.
* Collaborate with developers and teams to optimize workflows and processes in agile environments (e.g., Scrum, Kanban).
* Ensure scalability and reliability of all automated processes.
Requirements
* Hands-on experience with AWS services, including S3, RDS, Lambda, and serverless architectures.
* Proficiency in scripting and automation tools for streamlining workflows.
* A deep understanding of process optimization and integration development.
* Familiarity with agile methodologies and collaborative team environments.
* Strong analytical skills and a passion for efficiency and innovation.
* Nice to have: experience with hubspot
Benefits
* Above-average compensation
* Flexible working hours
* Free parking
* Home Office
* Mentoring sessions
* Remote work
We look forward to receiving your application! You can learn a lot during this internship and also take on responsibility yourself!
At PVision, we are pioneers in the development of innovative software solutions for analysing photovoltaic systems. Our technology enables electricians to efficiently identify damage to medium-sized systems using drone thermal imagery and AI-powered analysis. Through our subscription model, we provide a powerful tool that optimises the maintenance of PV systems and enables early detection of module damage.