Lead Software Engineer - Investment Analytics, VP - State Street Investment Management

Software Engineering Lead State Street Investment Management is seeking a highly experienced Software Engineering Lead to join our Investment Analytics Application Development team. The ideal candidate brings strong financial domain knowledge and deep technical expertise, with experience building and supporting systems that process, analyze, and deliver investment and financial data for portfolio management, research, risk, and reporting use cases. While experience with performance measurement and attribution is important, this role is broader in scope and suited for engineers who understand financial data holistically—returns, holdings, benchmarks, market data, and analytics workflows. You will work closely with portfolio managers, investment researchers, and technology partners to translate complex financial concepts into scalable, high‐quality solutions built on Databricks in AWS. This role is hands‐on and requires independent ownership of design and implementation. What You Will Be Responsible For Design, build, and optimize scalable applications and data pipelines using Python, PySpark, and SQL on Databricks (AWS).Partner with business stakeholders to understand financial data, analytics requirements, and downstream usage across research, portfolio management, risk, and reporting. Implement solutions that support financial analytics use cases, including (but not limited to) performance measurement, attribution, returns analysis, and benchmark comparisons. Participate in requirements analysis, solution design, and technical implementation following an Agile SDLC.Develop robust, maintainable data workflows with strong emphasis on data quality, transparency, and operational reliability. Optimize Spark and SQL workloads for scale and performance using appropriate partitioning, query design, and Databricks best practices. Own the investigation and resolution of complex production issues, including root‐cause analysis and long-term remediation. Collaborate with application, data architecture, and infrastructure teams to deliver end‐to‐end solutions. Contribute to technical standards, best practices, documentation, and design reviews. Remain current with emerging technologies and recommend improvements to tools, frameworks, and development practices. Responsible for collaborating with global team on sprint milestones. These Skills Will Help You Succeed in This Role Strong experience working with financial data in an asset management or capital markets environment, such as: Returns and performance data Holdings, transactions, and positions Benchmarks and market/reference data Performance and/or attribution concepts and calculations Advanced development skills in: Python, PySpark, and advanced SQLLarge-scale data processing and optimization Experience building solutions on Databricks / Apache Spark in a cloud environment (AWS preferred).Solid understanding of data warehousing and analytical data platform concepts. Strong analytical and problem-solving skills with the ability to work independently. Effective communicator able to collaborate across technical and non-technical stakeholders. Familiarity with BI and data visualization tools for enabling reporting and insight delivery. Experience leveraging AI‐assisted development tools to improve productivity and code quality. Education &