Portfolio Engineer

Job Description

The Portfolio Engineer in the Liquidity Management and Beta Implementation (LMBI) division will play a key role in building and maintaining the infrastructure that supports SWIB’s financing and investment activities. Reporting to the Head of LMBI, this role serves as a liaison between LMBI and SWIB’s technology teams to define, prioritize, and integrate the division’s data within SWIB’s broader technology architecture.

The Portfolio Engineer will be a primary contributor to system requirements, development of new functionality, and enhancement of existing tools. The role is responsible for producing and maintaining analytics and reporting that support investment analysis, risk management, value generation, and firmwide reporting. The ideal candidate combines strong investment knowledge with technical expertise and collaborates effectively across the organization to deliver scalable data, analytics, and reporting solutions.

This position requires a minimum of 3 days per week in our Madison, WI office.

• Develop and document high-quality production code to support portfolio management processes and reporting.
• Support implementation and ongoing management of investment strategies across asset classes.
• Enhance investment reporting related to performance, exposure, and risk.
• Collaborate with investment, risk, operations, and technology teams to optimize investment systems and infrastructure.
• Lead and champion strong data management practices within the division.
• Partner with SWIB technology and data teams to ensure alignment between divisional needs and enterprise architecture.

• Build and maintain reports and analytics to support investment and operational teams.
• Enhance division-wide and asset-class reporting for performance, attribution, exposure, and risk.
• Integrate data from multiple sources with varying granularity and frequency.
• Support standardized firmwide reporting and performance attribution analysis.
• Complete ad hoc analytical projects as assigned.

• Advanced degree in finance, quantitative finance, or a related field.
• Minimum of 3 years of post-degree experience (internships included).
• Strong understanding of asset allocation, performance attribution, and risk measurement.
• Proficiency in Python/Pandas (required); experience with Matlab, R, SQL, VBA, or C++ preferred.
• Experience with reporting tools such as Snowflake, Power
  
  BI, and/or Tableau.
• Knowledge of quantitative portfolio concepts and industry-standard performance and benchmarking practices.
• CFA, FRM, or progress toward a relevant professional designation preferred.
• Strong analytical, quantitative, and data management skills.
• Excellent communication, collaboration, and stakeholder engagement abilities.
• Adaptable, detail-oriented, and able to thrive in a fast-paced environment with a strong commitment to excellence.