Vacancy Description
Join Capgemini as a Senior Data Engineer, focusing on Databricks, Python, and PySpark to create comprehensive data solutions. This role demands strong expertise in building and maintaining high-performing data infrastructure.
In this pivotal role, you will be responsible for developing scalable data pipelines and orchestrating workflows using Apache Airflow. Your work will support the analytics engine of leading organizations, directly impacting their data strategies. Engage with diverse teams to ensure the quality and reliability of data systems.
Key Responsibilities:
• Develop scalable ETL/ELT data solutions
• Orchestrate workflows with Apache Airflow
• Enhance data processing on Databricks
• Conduct data ingestion from various sources
• Ensure data quality and governance across pipelines
Requirements:
• Proficiency in Python and PySpark
• Experience with Apache Airflow and Databricks
• Solid understanding of SQL and databases
• Familiarity with cl...
In this pivotal role, you will be responsible for developing scalable data pipelines and orchestrating workflows using Apache Airflow. Your work will support the analytics engine of leading organizations, directly impacting their data strategies. Engage with diverse teams to ensure the quality and reliability of data systems.
Key Responsibilities:
• Develop scalable ETL/ELT data solutions
• Orchestrate workflows with Apache Airflow
• Enhance data processing on Databricks
• Conduct data ingestion from various sources
• Ensure data quality and governance across pipelines
Requirements:
• Proficiency in Python and PySpark
• Experience with Apache Airflow and Databricks
• Solid understanding of SQL and databases
• Familiarity with cl...
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