Azure Data Factory Data Engineer — Scalable ETL Pipelines
Capgemini Engineering
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Benefits offered by this job
Job summary
Capgemini Engineering is seeking a Data Engineer with Azure Data Factory expertise to design, develop, and maintain scalable data pipelines. You will collaborate with data analysts, data scientists, and stakeholders to ensure reliable and optimized data for analytics and reporting.
The role requires 3+ years in data engineering, Python proficiency, and strong ETL/ELT knowledge, with familiarity in Azure services and Databricks.
Qualifications
- Bachelor’s degree in CS/Engineering/IS or related field.
- 3+ years of data engineering experience.
- Proficiency in Python.
- Strong understanding of ETL/ELT processes.
- Experience with Azure Cloud Services, especially Azure Data Factory.
- Ability to review monitoring reports and create PBIs for fixes.
Responsibilities
- Identify and troubleshoot root causes of failures in pipelines built with Azure Data Factory.
- Review team monitoring reports to identify issues and create corresponding PBIs for resolution.
- Monitor the status of Databricks jobs and ADF pipelines.
- Understand ETL and ELT concepts and apply them in design.
- Work with Azure Cloud Services, Azure Data Factory and Python / SPARK (Azure Databricks).
Skills
Education
Tools
Job description
Capgemini Engineering is seeking a Data Engineer with Azure Data Factory expertise to design, develop, and maintain scalable data pipelines. You will collaborate with data analysts, data scientists, and stakeholders to ensure reliable and optimized data for analytics and reporting.
The role requires 3+ years in data engineering, Python proficiency, and strong ETL/ELT knowledge, with familiarity in Azure services and Databricks.
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