Junior, Mid-Level
Data Engineer - eFraud
We are seeking a skilled Data Engineer to join the eFraud team and contribute to the development and evolution of our fraud detection platform. As part of our team, you will play an essential role in the innovation and creation process of Societe Generale software solutions that can reshape the digital world of tomorrow.
Your Role in a Nutshell:
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Carry out Big Data developments to meet eFraud business and technical needs, perform end-to-end testing by defining test scenarios and documenting defects, and support deployments to production.
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Collaborate with cross-functional teams to gather and analyze requirements, design solutions, and implement features that meet business needs.
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Design, develop and maintain data pipelines for extracting, transforming and loading data from different sources.
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Develop and maintain the data infrastructure (database, data warehouses, data lake) and data visualization tools.
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Help anticipate, investigate, and prevent production incidents affecting fraud detection microservices hosted on the Big Data platform (investigation, follow-up, and communication with all stakeholders involved).
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Participate in code reviews, providing constructive feedback and ensuring adherence to coding standards and best practices.
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Troubleshoot and debug issues, and implement fixes to ensure the stability, performance, and security of applications.
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Stay updated on industry trends and emerging technologies and continuously improve technical skills and knowledge.
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Build a strategy to reduce technical debt, improve security, and ensure the decommissioning of unused resources.
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Contribute to maintaining up-to-date documentation and ensuring compliance with data governance and data usage standards.
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Implement and monitor data quality controls, reconciliation mechanisms, and data observability processes.
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Ensure data lineage, traceability, and compliance with Group data governance standards.
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Contribute to the evolution of the data platform architecture, evaluating new technologies and best practices in Data Engineering, Cloud, AI, and Analytics.
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Explore opportunities to leverage AI and GenAI capabilities to improve fraud detection processes, data analysis, and engineering productivity.
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