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 to the implementation of the Group Data Platform, a hybrid platform for EDF's business units, combining on-premise infrastructure and GCP cloud services.

- Implementation of a hybrid data analytics architecture: Apache Trino on OpenShift, BigQuery on GCP, unified storage format in Iceberg.

- Deployment of orchestration and ETL components: Apache Airflow (on-premise) and Cloud Composer (GCP), Spark on Kubernetes via DCP.

- Integration of streaming services (Debezium Kafka Connect), indexing (Elasticsearch), and monitoring (Dynatrace).

- Development of a modular infrastructure via Terraform for deploying projects on GCP (BigQuery, Cloud Run, Cloud Form).

- Integration of visualization solutions (Power BI Online) and multi-technology storage: PostgreSQL DBaaS, Oracle (Exadata), Scality (S3), TDP (Hadoop).

- Definition and automation of access governance via OpenMetadata, ensuring data usage security and compliance.

- GCP logging monitoring to Dynatrace.