Kamel Benayad

Mission 1 : Role progression : Data Engineer → Tech Lead / Application Owner (SPOC) | Azure Data Platform (Agile SAFe) Role : Tech Lead / SPOC •Acted as the single point of contact for the application (technical + functional), owning the scope end-to-end. •E2E delivery of enhancements: requirements gathering, scoping, solution design, development, testing, release, and documentation. •Built Azure Data Factory pipelines, Azure Databricks workloads (Scala/SQL). •End-to-end orchestration with Control-M and CI/CD industrialization with Jenkins. •Run ownership: incident handling, RCA, fixes, monitoring, continuous improvement, and target architecture recommendations aligned with Group strategy. Impact: •Reduced E2E batch processing time from overnight to ~30 minutes. •Faster incident diagnosis and root-cause analysis (RCA) •Improved cost control (FinOps). Mission 2 : Redesign, migration, and industrialization of a legacy application (group internal billing) to the Azure cloud (Agile SAFe Part 1: Business Analyst • Functional referent of the application • Business support in the application mutation and parallel run phase • Write the specifications and interface contracts for entry and exit of the application • Receipt and management of achievements • Application scope management (application maintenance, functional analysis) • Communication with business lines and other project teams • Analysis of the old COBOL code of the application and determination of the management rules • Determination of calculation rules • Animation workshop around the new application • Participation in the division of the User Stories • Participation in PI planning Part 2: Cloud Data Engineer • Participation in the development of the new hybrid architecture of the new application (Data on prem to Azure) • Batch and HMI data ingestion • Implementation of part of the management rules • Realization of interface contracts for consumer applications • Animation of workshop on databricks and azure

Réalisation d’un MVP, implémentation d’une plateforme Data hybride autour d’un sujet DataLake Finance Les services PaaS • Ingestion : Az Copy, API Management • Stockage : Data Lake Store • Modélisation : Synapse Spark, Databricks, • Restitution : Power BI Premium, • Exploitation : Azure RBAC

Role : Data Engineer / Scientist Domain : Banking and finance Data engineering mission: Data Pipeline design Data Science mission: Prediction of transaction delivery delays

• Support for the business on Data & IA subjects (use cases). • Framing and animation of workshops. • End user training and Change Management. • Participation in Digital Center IA Projects • AI training path with Microsoft • Internal training Data Science with DXC University • POC realization • Participation in responses for tenders. • Participation in responses for tenders.

Role : Data IA engineer. Domain : Retails - telecommunications Retail Forecasting • Forecast sales of accessories and connected objects • Stock forecast • Creation of PowerBi dashboard

Participation in Digital Center IA Projects AI training path with Microsoft Internal training Data Science with DXC University POC realization