Farhane K.

As a Solutions Architect at Cloudera, my main mission is to help clients design and implement effective big data solutions using Cloudera's technology stack aka CDP. This involves a range of responsibilities, including: 1. Understanding client requirements: As a solutions architect, I work with customers to understand their specific needs, challenges, and goals. I ask questions and gather informations in order to design solutions that will meet their unique requirements. 2. Designing big data architectures: Based on my understanding of the client's needs, I create and propose architectures that will effectively manage and process their big data. This could include designing data storage systems, data processing pipelines, and analytics platforms. 3. Demonstrating technical expertise: Solutions architects at Cloudera need to have deep technical expertise in big data technologies and be able to articulate that expertise to clients. I often participate in conducting demos, create proof-of-concept projects, and provide technical guidance to clients as needed. 4. Collaborating with other teams: As a Solutions architect, I work closely with sales, engineering, and product management teams to ensure that solutions are designed and implemented effectively. I make collaborate effectively with others and communicate technical concepts to non-technical stakeholders. 5. Finally, one of my principles is Customer Obsession: I Ensure that clients are successful in their use of Cloudera's technologies. This means working closely with clients to troubleshoot issues, provide guidance, and offer training as needed to ensure they get the most out of the solutions you design.

Contribution à la mise en œuvre de la Plateforme Data Groupe, une plateforme

hybride destinée aux entités métiers d’EDF, combinant infrastructures on-premise et

services cloud GCP.

- Mise en place d’une architecture data analytique hybride : Apache Trino sur

OpenShift, BigQuery sur GCP, format de stockage unifié en Iceberg.

- Déploiement de composants d’orchestration et d’ETL : Apache Airflow (on-

premise) et Cloud Composer (GCP), Spark sur Kubernetes via DCP.

- Intégration des services de streaming (Debezium Kafka Connect), d’indexation

(Elasticsearch), et de monitoring (Dynatrace).

- Développement d’une infrastructure modulaire via Terraform pour le déploiement

de projets sur GCP (BigQuery, Cloud Run, Cloud Form).

- Intégration de solutions de visualisation (Power BI Online) et de stockage multi-

technologies : PostgreSQL DBaaS, Oracle (Exadata), Scality (S3), TDP (Hadoop).

- Définition et automatisation de la gouvernance des accès via OpenMetadata,

assurant la sécurité et la conformité de l’usage des données.

- Logging monitoring GCP vers dynatrace.