Azure Data Engineer: ETL Pipelines & Databricks Expert
Capgemini
An application made for this job — a tailored resume and cover letter that speak straight to the posting.
Job summary
Capgemini is seeking a skilled Data Engineer with expertise in Azure Data Factory to design, develop, and maintain scalable data pipelines and ETL processes. You will collaborate with data analysts, data scientists, and business stakeholders to ensure data is accessible, reliable, and optimized for analytics and reporting.
The role emphasizes hands-on data engineering in Azure, Python, and Databricks, with a focus on production-grade pipelines and strong ownership of data quality and performance.
Qualifications
- Bachelor's degree in CS, Engineering, IT 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 Data Factory and Azure Cloud Services.
- Ability to review monitoring reports and create PBIs for fixes.
- Focus on system maintenance.
Responsibilities
- Identify and troubleshoot root causes of failures in pipelines built with Azure Data Factory.
- Review monitoring reports to identify issues and create PBIs for resolution.
- Monitor the status of Databricks jobs and ADF pipelines.
- Understand ETL and ELT concepts and approaches.
- Work with Azure Cloud Services, Azure Data Factory and Python / SPARK (Azure Databricks).
Skills
Education
Tools
Job description
Capgemini is seeking a skilled Data Engineer with expertise in Azure Data Factory to design, develop, and maintain scalable data pipelines and ETL processes. You will collaborate with data analysts, data scientists, and business stakeholders to ensure data is accessible, reliable, and optimized for analytics and reporting.
The role emphasizes hands-on data engineering in Azure, Python, and Databricks, with a focus on production-grade pipelines and strong ownership of data quality and performance.
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