Python Data Engineer - AVP - C12 - Pune

As a Full Stack Data Scientist / Data Engineer at Citi's Global FX Team, your role will involve: - Designing, developing, and implementing quantitative models to derive insights from large and complex FX datasets, focusing on market trends, client behavior, revenue opportunities, and optimizing the FX business. - Engineering data and analytics pipelines using modern, cloud-native technologies and CI/CD workflows to ensure consolidation, automation, and scalability. - Collaborating with stakeholders across sales and trading to understand data needs, translate them into impactful data-driven solutions, and deliver these in partnership with technology. - Developing and integrating functionality to ensure adherence with best practices in terms of data management, need-to-know (NTK), and data governance. - Contributing to shaping and executing the overall data strategy for FX in collaboration with the existing team and senior stakeholders. Qualifications required for this role include: - 8 to 12 years of experience - Masters degree or above in a quantitative discipline - Proven experience in software engineering and development, with a strong understanding of computer systems and their operation - Excellent Python programming skills, including experience with relevant analytical and machine learning libraries (e.g., pandas, polars, numpy, sklearn, TensorFlow/Keras, PyTorch), visualization, and API libraries (matplotlib, plotly, streamlit, Flask) - Experience developing and implementing Gen AI applications from data in a financial context - Proficiency working with version control systems such as Git and familiarity with Linux computing environments - Experience with different database and messaging technologies such as SQL, KDB, MongoDB, Kafka - Familiarity with data visualization and ideally development of analytical dashboards using Python and BI tools - Excellent communication skills, both written and verbal, with the ability to convey complex information clearly and concisely to technical and non-technical audiences - Ideally, some experience working with CI/CD pipelines and containerization technologies like Docker and Kubernetes - Ideally, some familiarity with data workflow management tools such as Airflow and big data technologies such as Apache Spark/Ignite or other caching and analytics technologies - A working knowledge of FX markets and financial instruments would be beneficial.