Descripción breve
Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like, where you’ll be supported and inspired by a collaborative community of colleagues around the world, and where you’ll be able to reimagine what’s possible. Join us and help the world’s leading organizations unlock the value of technology and build a more sustainable, more inclusive world.
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.