Mohamed Messaad

Conception et implémentation d'une API en Go, utilisant PostgreSQL et Redis comme Datastore:

- Mise en place de la spec API (OpenAPI spec)

- Implémentation d'une API + tests unitaires associés

Re-designed and implemented a gaming center's infrastructure by designing a secure and scalable hybrid cloud system, integrating on-premise and Cloud Kubernetes components with secure networking between Cloud and on-premise components of the system.

- Implemented cutting-edge GitOps and CI/CD tooling and processes to enhance development team efficiency, allowing for quick, safe, and reliable iterations: ArgoCD, Github Actions

- Deployed a scalable, cost-effective logging and observability solution by integrating state of the art Open Source components: Elasticsearch, Kibana, Prometheus, Grafana, and Telegraf

- Contributed to refactoring and porting a back-end service from Python to Golang.

- Tackled intricate infrastructure challenges, including setting up secure networking between multiple sites (Cloud and on-premise).

Founding member of the Data team at Gorgias. In the Data team, I worked on designing, implementing and deploying to production a Change Data Capture architecture to build up-to-date (less than 1 minute latency) search indexes on Elasticsearch, consisting in a denormalized representation of multiple large (several TBs per table, 100,000,000s of rows) tables from our relational databases (PostgreSQL), including:

- Deployed, tuned and managed Debezium instances to emit CDC events from the source database when changes happen on a set of table (multiple deployments running on our multiple Kubernetes clusters, deployed and managed via Terraform)

- Designed, implemented and deployed streaming data pipelines using Apache Beam (Python) that consume high throughput (up to 1000 events/s) streams of CDC events and build an eventually-consistent, denormalized view of the source database, indexed in Elasticsearch, with less than 1 minute of latency between the consumption of events and them being reflected in the target search index

- Deployed, maintained and scaled large Elasticsearch deployments (500GB/ index) across multiple regions using Terraform for provisioning and day-to-day changes

- Designed and optimized large Elasticsearch indexes containing 100,000,000s of documents in terms of both ingest and search performance.