Ramzi Houidi

Designed and implemented a cloud-native data platform on Azure Kubernetes Service (AKS) using GitOps principles with ArgoCD. Built microservices-based data applications, designed secured configurations, and constructed resilient ETL pipelines. Provided leadership for a team while implementing DevOps and IaC frameworks for the first time in the organization. Achievements: - Designed a robust cloud-native architecture with AKS, Azure SQL, Oracle, and Azure Storage. - Implemented GitOps CI/CD pipelines with ArgoCD and Helm for automated deployments. - Integrated Azure Key Vault for secrets management and configured workload identity for secure pod authentication. - Built containerized Python ETL pipelines and batch jobs using Kubernetes CronJobs. - Configured health checks, probes, resource quotas, and auto-scaling to ensure reliability and performance. - Led the team in establishing container image versioning, configuration management, and deployment patterns. - Delivered observability and monitoring using Azure Application Insights. Technical Environment: Azure Kubernetes Service (AKS) | Azure SQL | Oracle | Azure Storage | Python | Helm | ArgoCD | Azure Key Vault | GitOps | Kubernetes CronJobs | Application Insights | Docker | CI/CD | IaC

Conception, implementation, and migration of data warehouse to BigQuery. Achievements: - Designed a robust data architecture tailored to meet specific requirements for Belmond. - Developed efficient data transformation workflows using Dbt, Dataform and Workflows. - Actively participated in sprint planning sessions, ensuring smooth project execution. - Implemented BigQuery for storing and managing data, ensuring scalability and reliability. - Configured GCP infrastructure using Terraform, optimizing resource allocation. - Successfully migrated existing data to BigQuery, ensuring data quality and integrity. - Optimized query performance to enhance efficiency and reduce storage costs. - Implemented a caching solution using Firestore for faster data retrieval. Technical Environment: BigQuery | DBT | Firestore | Dataform | Python | Terraform | GCP | Docker | GIT | Fivetran | Agile Scrum

Implementation and improvement of a Data Platform (Collibra): - Define and implement complex Data Management using GCP BigQuery & Collibra. - Implementation of standard and custom connectors to ingest metadata from various source systems. - Data integration. - Data quality ingestion into Collibra. - DevOps environment with Terraform, GCP Cloud Build, and Github. Achievements: - Participated in sprint planning (3 weeks). - Implemented datamarts in BigQuery. - Developed various APIs for data ingestion, reading, formatting, and creation. - Extracted technical metadata from BigQuery. - Created a workflow using Cloud Workflows. - Implemented data quality tools. - Created diverse dashboards using Google Data Studio. - Monitored the workflow and metadata. Technical environment: - Agile Scrum methodology. - Python (3.8), Poetry, Sanic Open API. - Terraform, Cloud Scheduler, App Engine, Cloud Run, Docker, Cloud Storage. - Google Data Studio, GIT, Collibra.

- Design and deployment of a serverless event-driven system with AWS API Gateway, AWS Lambda, and AWS Kinesis. - Design and implementation of a Data Lake on AWS based on S3. - Using Spark for Data transformation Using AWS EMR and AWS Glue. - Automation of deployments using Terraform. - Implementation of a continuous integration and deployment process with Gitlab CI / CD.

Develop and manage cloud systems (mainly on Google Cloud Platform) for various data science projects: • Ad hoc analysis via SQL / Python. • Deploy data pipelines ETLs using GCP. • Maintain code quality through Gitlab CI / CD pipelines. • Infrastructure deployments.

Development of Social Network for doctors and medical company to interact, learn and share their knowledge. Keywords: Ionic 3 ,Angular 4,TypeScript,PHP,MySql