Python Engineer
Location: Remote
Contract
I am currently working with a leading hedge fund that is looking for a strong Python Engineer to join their growing technology team. The role focuses on building robust data and analytics tools that support investment, trading, and risk functions across the firm, with particular emphasis on fixed income and credit markets.
Role Overview
You will be responsible for developing and enhancing Python-based systems used across the investment lifecycle. The ideal candidate will have strong Python skills, solid experience working with financial markets data, and good knowledge of fixed income products such as bonds, rates, or credit instruments.
This is a hands-on engineering role with a strong data focus, working closely with front-office and technology stakeholders.
Key Responsibilities
• Develop and maintain Python applications and internal tools used by investment and risk teams
• Build reliable ETL/ELT pipelines for financial, market, and operational datasets
• Work with structured financial data, market data feeds, and fixed income datasets
• Collaborate with traders, analysts, and technologists to understand workflow needs
• Integrate pricing, analytics, or risk libraries into internal systems
• Create automation and scripting tools to improve efficiency
• Implement best practices in testing, documentation, version control, and deployment
• Support the enhancement of data quality, reliability, and performance across systems
Required Skills & Experience
Essential:
• Strong hands-on Python programming experience
• Background in investment banking, hedge funds, or financial markets
• Good understanding of fixed income (bonds, credit, rates)
• Experience building ETL/ELT pipelines and handling large datasets
• Strong SQL skills and familiarity with structured data environments
• Experience working with trading, risk, or analytics systems
• Strong communication and ability to work closely with front-office and data teams
Desirable:
• Experience with fixed-income analytics or pricing libraries
• Exposure to credit products, market data feeds, or time-series data
• Familiarity with cloud technologies or distributed data systems
• Experience with automation, scripting, and workflow optimisation