Python Data Engineer

Key Responsibilities: Analyze data modernization strategies and implement scalable, high-quality data solutions. Develop data engineering solutions using Python, Pandas, SQL, and relational databases. Translate business requirements into detailed technical specifications. Build and support distributed applications, microservices, and RESTful APIs. Collaborate with cross-functional teams in an Agile environment using Jira. Support application deployment and development workflows using Git, Jenkins, and automation tools.

Required Skills: Strong Python programming experience, particularly with Pandas and data engineering. Strong SQL skills, preferably with SQL Server. Experience building distributed applications and data-driven solutions. Familiarity with relational databases such as SQL Server, Oracle, or DB2.Understanding of microservices architecture and RESTful API development. Experience with Git, Jenkins, and software deployment tools. Experience working in an Agile development environment.

Preferred Qualifications: Experience in capital markets, particularly market risk or counterparty credit risk. Knowledge of derivatives, financial product data modeling, and risk management. Experience with Test-Driven Development (TDD).Exposure to Generative AI (GenAI) and Agentic AI.

Skills: jenkins, pandas, data engineering, distributed applications, python, microservices, investment banking technology team, data, sql, databases