Python Data Engineer

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.

Requirements

• 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.

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