Senior Python Developer – Risk & Banking Domain

Descrição da Vaga

Requisitos

• We are seeking an experienced Senior Python Developer with strong expertise in data processing, SQL, and risk modeling within the banking domain
• The ideal candidate will have extensive hands-on experience in building data-driven solutions, applying data modeling techniques, and supporting financial risk and liquidity analysis
• 6+ years of hands-on experience in Python development
• Strong expertise in SQL and data manipulation techniques
• Proven experience in the banking or financial services domain
• Solid understanding of risk modeling and liquidity concepts
• Experience applying data modeling techniques and working with data models
• Familiarity with Agile methodologies
• Strong analytical and problem-solving skills
• Solid educational background from a reputed university

Responsabilidades

• This role requires a professional who can work closely with business stakeholders, risk teams, and technology groups to develop scalable data solutions and analytical models
• The consultant will be responsible for designing and implementing robust data pipelines, performing complex data manipulations, and contributing to risk modeling initiatives
• The selected candidate will play a key role in developing Python-based applications, optimizing SQL queries, and supporting liquidity and risk management functions in an Agile environment
• Develop and maintain Python-based applications for data processing and analysis
• Write and optimize complex SQL queries for data extraction and manipulation
• Design and implement data models and data modeling techniques
• Support development and enhancement of risk models and analytical frameworks
• Work on liquidity risk analysis and reporting within the banking domain
• Collaborate with business, risk, and technology teams to gather requirements
• Ensure data accuracy, consistency, and integrity across systems
• Participate in Agile development processes including sprint planning and reviews
• Analyze large datasets to generate insights for financial decision-making
• Enhance performance and scalability of data-driven applications