Yazid Djaoudi

Led the end-to-end engineering of a global, mission-critical data platform used across EDF Renewables’ international portfolio - spanning Europe, North America etc. Operated in a highly complex and sensitive industrial environment, enabling cross-continent teams to scale operations, standardize metadata, and unlock advanced use cases for hundreds of renewable energy assets worldwide.

• Led the design and implementation of a large-scale, serverless data platform on

AWS, enabling advanced industrial use cases across hundreds of EDF Renewables assets.

• Built a high-performance central API enabling clients to access unified metadata, trigger data pipeline operations, and allow business teams to upload complex configuration files through an associated frontend.

• Developed and optimized advanced parsing and validation workflows for domain - specific configuration files, including algorithmic optimizations and performance-critical processing paths.

• Designed new workflows end-to-end to support evolving business use cases,

ensuring scalability and maintainability.

• Implemented a hybrid storage strategy: DynamoDB for high-speed ingestion and

locking mechanisms, PostgreSQL as the system’s source of truth, and Delta Tables for downstream consumption (Databricks, data pipelines, analytics).

• Engineered a microsecond-level ingestion system with a robust, distributed locking mechanism ensuring exactly-once activation.

• Built event-driven communication between services using AWS EventBridge,

enabling decoupled, reactive microservices.

• Deployed a fully serverless architecture leveraging Lambda, API Gateway (or Load Balancer), VPC networking, and other AWS managed services to eliminate

infrastructure overhead.

• Managed complex multi-environment deployments (SBX, STG, PRD) using

Terraform + Terragrunt for full Infrastructure as Code.

• Exposed curated datasets on Databricks for advanced analytics and downstream ML/data engineering pipelines.

The Beauty Tech Data Platform is L'Oréal's famous asset that empower the business through Data. As a Data Engineer inside the Product team (biggest Data team), I'm in charge of updating and creating tables that many users/use cases use daily. Quick summary

• Sourcing new data sources (API, SQL, Datalake, SAP…)

• Creating and updating tables from the 3 layers (SDS, SDDS, CD)

• Source domain dataset (SDS)

• Shared domain dataset (SDDS)

• Consumption dataset (CD)

• Production releases every week

• Development of new workflows through the L'Oréal's framework

Creating a Data platform to handle data of a French media company.

Quick summary

• Architecturing the Data pipeline (GCP)

• Creating and implementing the Data Pipeline on GCP

• Creation of a Data lake and different layer (Bronze, Silver & Gold)

• Data processing (Cloud Dataflow = Apache Beam)

• Analytics and KPI calculation (BigQuery)