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Data Engineer Databricks Expertise
Job Description & How to Apply Below
Capgemini seeks a Data Engineer proficient in Databricks, Apache Airflow, Python, and PySpark to design high-performance data solutions. This role emphasizes building efficient data pipelines and ensuring data reliability.
As a Senior Data Engineer at Capgemini, you will leverage your expertise to construct scalable ETL/ELT data pipelines and manage workflow orchestration. Your contributions will help major organizations transform their operations through smart data management. Collaboration with analysts and scientists is essential for delivering comprehensive data solutions.
Key Responsibilities:
• Design and maintain scalable ETL/ELT data pipelines
• Build workflows using Apache Airflow
• Optimize data processing solutions on Databricks
• Monitor and troubleshoot job performance issues
• Collaborate with analysts and business stakeholders
Requirements:
• Strong experience in Python programming
• Expertise in PySpark and Apache Spark
• Familiarity with Apache Airflow
• Practical knowledge of Databricks platform
• Understanding of ETL/ELT concepts and data architecture
Bring your data engineering skills to Capgemini and contribute to impactful data-driven solutions.
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