**Company Description** We are **Inetum**, a European leader in digital solutions. With a team of more than 28,000 consultants and experts, we strive every day to fulfill our purpose: achieving digital impact in businesses faster, easier, and for the benefit of everyone. At Inetum, we support our collaborators on their path to success. If you enjoy reinventing yourself and solving problems with new strategies, working on innovative technology and business projects, **apply now!** **Requirements*** 3 or more years of experience implementing cloud solutions (regardless of the cloud provider) using the required technologies, having performed the following activities: * Analysis and development of data ingestion and transformation workflows in Lake House using Cloud services. * Analysis and development using distributed processing in Spark using PySpark/Spark in batch (mandatory) and Realtime (desirable). * Optimization of processes to be developed or existing ones with a cost-reduction focus (processing time, cluster usage, and Azure services) in cloud service consumption. * Analysis and scheduling of processes according to user-defined criteria. * Deployment of solutions into production using continuous integration and deployment tools (DevSecOps). * Development of cross-cutting solutions for continuous improvement of the development and deployment framework. * Development of best practices, frameworks, and development standards on Cloud platforms. * Possession of the following Azure certifications (desirable) or equivalent certifications in other clouds: * Databricks: Databricks Certified Associate Developer for Apache Spark (desirable) * Azure: Azure Data Engineer Associate and Data Engineer Professional (desirable) * Agile methodology (in projects). * 3 or more years of experience working on at least 2 of the following Cloud projects: * Analyzing and processing large volumes of data * Building data pipelines, ETL, ELT * Deploying scalable solutions into production, preferably within banking institutions * Migration of processes to Cloud platforms * Optimization of processes using distributed processing