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Data Engineer

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**Data Engineer (México, Remote)**At Capgemini Engineering, the world leader in engineering services, we bring together a global team of engineers, scientists, and architects to help the world’s most innovative companies unleash their potential. From autonomous cars to life-saving robots, our digital and software technology.**Responsabilities**:- Identify and troubleshoot root causes of failures in pipelines built with Azure Data Factory.- Review team monitoring reports to identify issues and create corresponding User STpries / PBIs for resolution.- Monitor the status of Databricks jobs and ADF pipelines.- Understand the concepts of ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform) processes.- Work with Azure Cloud Services, Azure Data Factory and Python / SPARK (we use Azure Databricks).**Qualifications**:- Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field.- 3+ years of experience in data engineering or related role.- Proficiency in Python.- Strong understanding of ETL/ELT processes.- Experience with Azure Cloud Services specially in Azure Data Factory.- Ability to review monitoring reports and create PBIs for necessary fixes.- Focus on system maintenance.**Prefered qualifications**:- Azure certifications (e.g., Azure Data Engineer Associate).- Experience with Databricks, Power BI, or Azure DevOps.- Experience working in Agile/Scrum environments.Capgemini is a global leader in partnering with companies to transform and manage their business by harnessing the power of technology. The Group is guided everyday by its purpose of unleashing human energy through technology for an inclusive and sustainable future. It is a responsible and diverse organization of over 300,000 team members in nearly 50 countries. With its strong 50-year heritage and deep industry expertise, Capgemini is trusted by its clients to address the entire breadth of their business needs, from strategy and design to operations, fueled by the fast evolving and innovative world of cloud, data, AI, connectivity, software, digital engineering and platforms.