Python Data Engineer

As a Full Stack Data Scientist / Data Engineer at Citi's Global FX Team, you will be part of the FX Data Analytics & AI Technology team responsible for developing and implementing data-driven models and engineering robust data and analytics pipelines to extract actionable insights from global FX data. Your role will involve collaborating with stakeholders across sales, trading, and technology to drive the overall data strategy for FX. **Key Responsibilities:** - Design, develop, and implement quantitative models to analyze large and complex FX datasets, focusing on market trends, client behavior, revenue opportunities, and business optimization. - Engineer data and analytics pipelines using modern cloud-native technologies and CI/CD workflows for consolidation, automation, and scalability. - Collaborate with sales and trading teams to understand data requirements, translate them into impactful solutions, and deliver in partnership with technology. - Ensure adherence to best practices in data management, need-to-know (NTK), and data governance. - Contribute to shaping and executing the overall data strategy for FX in collaboration with the existing team and senior stakeholders. **Qualifications Required:** - 8 to 12 years of experience in a relevant field. - Masters degree or above in a quantitative discipline. - Proven expertise in software engineering, development, and a strong understanding of computer systems. - Excellent Python programming skills with experience in relevant analytical and machine learning libraries. - Proficiency in version control systems like Git and familiarity with Linux computing environments. - Experience with database technologies such as SQL, KDB, MongoDB, messaging technologies like Kafka, and data visualization tools. - Strong communication skills to convey complex information clearly to technical and non-technical audiences. - Ideally, experience with CI/CD pipelines, containerization technologies like Docker and Kubernetes, and data workflow management tools such as Airflow. - Working knowledge of FX markets and financial instruments would be advantageous. As a Full Stack Data Scientist / Data Engineer at Citi's Global FX Team, you will be part of the FX Data Analytics & AI Technology team responsible for developing and implementing data-driven models and engineering robust data and analytics pipelines to extract actionable insights from global FX data. Your role will involve collaborating with stakeholders across sales, trading, and technology to drive the overall data strategy for FX. **Key Responsibilities:** - Design, develop, and implement quantitative models to analyze large and complex FX datasets, focusing on market trends, client behavior, revenue opportunities, and business optimization. - Engineer data and analytics pipelines using modern cloud-native technologies and CI/CD workflows for consolidation, automation, and scalability. - Collaborate with sales and trading teams to understand data requirements, translate them into impactful solutions, and deliver in partnership with technology. - Ensure adherence to best practices in data management, need-to-know (NTK), and data governance. - Contribute to shaping and executing the overall data strategy for FX in collaboration with the existing team and senior stakeholders. **Qualifications Required:** - 8 to 12 years of experience in a relevant field. - Masters degree or above in a quantitative discipline. - Proven expertise in software engineering, development, and a strong understanding of computer systems. - Excellent Python programming skills with experience in relevant analytical and machine learning libraries. - Proficiency in version control systems like Git and familiarity with Linux computing environments. - Experience with database technologies such as SQL, KDB, MongoDB, messaging technologies like Kafka, and data visualization tools. - Strong communication skills to convey complex information clearly to technical and non-technical audiences. - Ideally, experience with CI/CD pipelines, containerization technologies like Docker and Kubernetes, and data workflow management tools such as Airflow. - Working knowledge of FX markets and financial instruments would be advantageous.