Jordy Bayo

• Facilitate daily meetings to ensure each team member shares their progress, identifies obstacles, and aligns priorities.

• Organize and facilitate sprint planning meetings, helping the team break down the backlog into actionable tasks and define clear goals for each sprint.

• Conduct sprint review meetings to assess progress, demonstrate new features to stakeholders, and gather constructive feedback.

• Facilitate sprint retrospectives to identify areas for improvement, celebrate successes, and develop action plans for future sprints.

• Collaborate closely with the Product Owner to prioritize backlog items based on business value and stakeholder needs.

• Facilitate communication between the Product Owner and the development team to ensure requirements are clearly understood and well-defined.

• Coordinate efforts between different development teams, network engineers, and maintenance technicians to ensure seamless integration of different project components.

• Maintain transparent and regular communication with stakeholders, providing updates on project progress and addressing their concerns and suggestions.

• Assist in identifying and removing obstacles that may hinder team progress, thereby facilitating smooth project progression.

• Promote a culture of continuous improvement within the team by implementing agile practices and tools to enhance efficiency and quality of deliverables.

• Oversee the design of the network analysis system architecture, ensuring it meets the technical and operational needs of the plant.

• Identify and analyze automation needs and application deployments and Kube (JAVA ABJ, AKJ).

• Translate functional requirements by creating an internal deployment CLI with Golang (a first at the Software Factory) allowing a reduction from 30min to 3min in application deployment time.

• Create and maintain CI/CD pipelines for code deployment using GitLab CI on Golang projects.

• Develop scripts to generate RPMs and use Trivy to analyze vulnerabilities in artifact releases intended for testing and production.

• Orchestrate the transition of knowledge from departing developers, securing essential expertise through detailed documentation and sharing sessions. This initiative facilitated the migration to newer technologies, in line with our evolution strategy: moving from Red Hat 7 to Red Hat 8, adopting GitLab CI to replace Jenkins, replacing Nexus with Artifactory, and optimizing deployments via Ansible and Argo CD, etc.

• Create CLIs for deployments to targets via Ansible Tower for developers using Golang, Cobra, and VIPER.

• Manage the migration of several old internal tools and reduce technical debt.

• Migrate RPM generation scripts from Red Hat 7 to Red Hat 8.

• Migrate code repositories from SVN to Git for the 2009 POC information systems of connected gas meters.

• Install and configure Squash AUTOM for the Corail teams, on several K8s clusters.

• Create KUIPER CLI, a deployment tool that automates tests, builds AKJ artifacts, and initiates deployments via the Kuiper API for Kubernetes applications with Helm charts at the end of the CI, following the success of ADA CLI.

• Develop scripts interacting with the Kubernetes API Server to extract Namespace UIDs from their names and associated clusters.

• Deploy and maintain machine learning models in production, specializing in plant disease detection, ensuring their continuous performance and reliability.

• Create and maintain CI/CD pipelines for code deployment using GitHub Actions on Flutter.

• Implement a Machine Learning pipeline to transfer field images and videos from a device to the cloud, store them in GCP buckets, and feed a GCP model for training and prediction of plant diseases from the provided images.

• Model the database for Firebase, including Real-Time Database and Firestore.

• Lead the migration of data and infrastructure from Salesforce and Heroku to GCP (Firebase), transitioning from a conceptual SQL model to NoSQL. This change addressed the need to optimize for a higher volume of reads (ML data stream) than writes and the flexibility to add new elements to tables without having to rework the model each time.

• Perform this migration by developing an advanced Python script. This script, executed as an administrator, established connections to Salesforce and GCP, facilitating data transfer every Saturday.

• Refactor Backend code (Python).

• Design and implement a CI/CD process for Flutter, enabling full automation of testing phases, APK compilation, and release version generation. This initiative improved development efficiency by ensuring fast and reliable deliveries, while minimizing the risk of manual errors. Thanks to this infrastructure, we were able to accelerate the release cycle, thus providing frequent and high-quality updates to our end-users.

• Integrate various GCP services, such as Cloud Vision for image analysis.