Sr. Software Engineer - Python

Senior Software Engineer — Investment Risk and Analytics. An institutional investment management firm is seeking a Senior Software Engineer to help develop the platforms supporting its investment analytics, quantitative research, and risk management capabilities. The firm designs and manages customized investment strategies across multiple asset classes. Its collaborative environment offers opportunities to learn from experienced professionals, contribute meaningful work, and grow professionally. Successful candidates bring strong analytical skills, intellectual curiosity, and a collaborative mindset.

Responsibilities

• Design, develop, and maintain Python platforms supporting investment analytics, quantitative workflows, and risk valuation.
• Partner with business stakeholders and quantitative researchers to understand needs and translate them into technical requirements.
• Build extensible solutions for data distribution, analysis, and modeling used by internal teams.
• Support the reliability, scalability, and performance of business-critical production systems.
• Participate in architecture discussions, design reviews, and code reviews.
• Collaborate across technology teams and mentor junior engineers.

Required Qualifications

• Bachelor's degree or equivalent experience in Computer Science, Engineering, Mathematics, Finance, Information Systems, or another analytical discipline.
• At least five years of professional software development experience, including three or more years working with Python.
• Extensive experience designing queries and data structures for relational databases, such as PostgreSQL or SQL Server.
• Experience building and operating business-critical production systems.
• Experience developing scalable systems, including monitoring and optimizing computational and memory performance.
• Experience with unit and integration testing frameworks and modern continuous integration and delivery practices.

Preferred Qualifications

• Experience collaborating with data scientists, quantitative researchers, or similar technical stakeholders.
• Experience developing solutions on AWS, Azure, or Google Cloud.
• Experience designing and implementing data pipelines for quantitative research, including backtesting, feature engineering, factor research, or portfolio analytics.
• Familiarity with C# or Java.
• Familiarity with MATLAB.
• Working knowledge of modern application frameworks.
• Professional experience in financial services.