Principal Front Office Engineer, Investments Technology (Private Equity/Private Credit)

• We are seeking a highly skilled and motivated Principal Front-Office Engineer to join our prestigious investment firm. As a Principal Front-Office Engineer, you will serve as the technical lead embedded within a Private Equity and Private Credit investment team, driving design and implementation of small-scale applications and proof of concepts that will improve market analysis, develop investment strategies, and enhance decision-making processes.

•  

•  

  You will partner directly with portfolio analysts and traders, but your primary focus will be building robust systems and tools that power investment decisions. We’re looking for a hands-on software architect and builder who has experience designing systems, rapidly iterating over them and delivering them across the finish line.
  
  This role is ideal for a Lead or Senior Engineer who thrives as an individual contributor and wants to drive technical direction without moving into management.

•  

•  

  Note: This Boston-based role has a hybrid work arrangement (2 days per week in office).

Hiqhly qualified candidates will have:

• Excellent problem-solving skills, with the ability to think critically, independently, and act with minimal handholding.
• Effective communication skills, with the ability to clearly articulate complex ideas and analysis to both technical and non-technical stakeholders.
• Strong attention to detail, organization, and the ability to manage multiple tasks and priorities in a fast-paced environment.
• Full-stack development knowledge with a minimum of 5 years professional experience programming in Python demonstrating the ability to write efficient and robust code able to process and analyze large financial datasets.
• Experience with key Python Libraries (pandas, NumPy) required
• Experience in front-end development and user experience (UX) design required; experience with Pythonic front-end and data visualization libraries (e.g., Plotly, Dash) preferred.
• Experience using Version Control (Git) required.
• Proven ability to design, build, and scale application systems in data-rich environments.
• Strong SQL skills required with a familiarity of financial data platforms (such as Bloomberg, FactSet, Aladdin, eFront), financial databases, and data manipulation techniques preferred. Experience with statistical and time-series data analysis using pythonic libraries (such as Scikit-Learn, SciPy, cvxpy) is preferred.
• Solid understanding of financial markets and willingness to learn the Private Equity and Private Credit domains.
• Practical experience in developing and maintaining models, tools, and reports that showcase a deep understanding of quantitative techniques, methods, statistics and econometrics