State Street Investment Management
Investment Management
SoftwareEngineeringLead–InvestmentAnalytics,VP
“Software Engineering Lead – Investment Analytics, VP at State Street Investment Management. Skills: Python, PySpark, SQL, Databricks, AWS, financial data analysis, performance measurement, attribution. 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”
What You'll Achieve.
deliver end‑to‑end solutions; improve productivity and code quality
Industry & Context.
analytical and problem-solving skills; Own the investigation and resolution of complex production issues; root-cause analysis
What They're Looking For.
Must Have
10+ years of experience delivering technology solutions, Bachelor’s degree in Computer Science, Computer Engineering, or equivalent practical experience, written and verbal communication skills, experience working with financial data in an asset management or capital markets environment, 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 SQL, Large-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, analytical and problem-solving skills with the ability to work independently, Effective communicator able to collaborate across technical and non-technical stakeholders
Nice to Have
experience with performance measurement and attribution, AWS preferred, 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
What You'll Do.
and optimize scalable applications and data pipelines using Python
and SQL on Databricks (AWS)
Partner with business stakeholders to understand financial data
analytics requirements
and downstream usage across research
Implement solutions that support financial analytics use cases
including (but not limited to) performance measurement
and benchmark comparisons
Participate in requirements analysis
and technical implementation following an Agile SDLC
maintainable data workflows with emphasis on data quality
and operational reliability
Optimize Spark and SQL workloads for scale and performance using appropriate partitioning
and Databricks best practices
Own the investigation and resolution of complex production issues
including root-cause analysis and long-term remediation
Collaborate with application
and infrastructure teams to deliver end‑to‑end solutions
Contribute to technical standards
Remain current with emerging technologies and recommend improvements to tools
and development practices
Responsible for collaborating with global team on sprint milestones
How You'll Work.
Team & Collaboration
Partner with business stakeholders; Collaborate with application, data architecture, and infrastructure teams; Contribute to design reviews; Collaborating with global team on sprint milestones
Communication Scope
Effective communicator able to collaborate across technical and non-technical stakeholders; written and verbal communication skills
Process & Methodology
Agile SDLC
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