• Migrated an IoT data platform from Azure VMs to a scalable architecture in AWS by designing and delivering Python microservices in ECS and EKS for the data pipeline resulting in a 60% decrease in costs and 80% decrease in processing time.• Automated the deployment of pipeline components and their configurations using Ansible. Also implemented a useful monitoring room using Prometheus and Grafana that monitors the whole platform components.• Built and maintained cloud infrastructure using Terraform. Developed CI/CD pipelines in GitLab for automated deployment of microservices in AWS. Implemented an eficient monitoring and alerting solution using Amazon Managed Prometheus, Grafana, and SES which notifies the responsible teams in email.• Developed Cloud-Native applications with Kotlin for managing customers and IoT devices which replaced the old BE platform, increased API performance by more than 70% and significantly reduced load and slow queries to InfluxDB.• Microservices integration with Keycloak for identity management and with Kafka for CQRS implementation.• Test-driven development using jUnit and testcontainers.• Replaced an old IoT data collector tool, made in Python, with Telegraf, a data collector agent, that gathers metrics from IoT devices through the MQTT protocol, process and transform the data using Starlark, and then store them in InfluxDB. This solution ensured more reliability of the data pipeline and reduced the number of lost messages by more than 80%.• Desinged and implemented a data pipeline POC leveraging Airflow and Metabase behind an Emissary-ingress in Kubernetes using Terraform as IaC.

• Implemented BE applications with Docker, FlaskAPI, and PostgreSQL.• Built ML models using pandas, matplotlib, seaborn and scikit-learn.