Senior Analyst, Data Engineering & Investment Analytics

About the role

We're looking for someone who lives at the intersection of data engineering and investment analytics. You'll be equally comfortable building a production data pipeline in Python and presenting portfolio analytics insights to a CIO.

Responsibilities

• Partner with investment professionals (PMs, CIOs, COOs, Heads of Operations) to understand their analytical needs and translate them into data products
• Build customized dashboards, analytics tools, and quantitative investment applications
• Present data-driven insights and recommendations to senior client stakeholders
• Identify opportunities where better data infrastructure can improve investment processes
• Design and implement scalable data platforms (data warehouses, data lakes) and end-to-end data pipelines for investment firms
• Develop and optimize production-grade code (Python/SQL) for data transformation and financial analysis
• Build and maintain data models that support portfolio analytics, risk reporting, and investment operations
• Leverage AI-assisted development tools to accelerate delivery

Requirements

• 5+ years of hands-on experience in a role that combined data/analytics engineering with business analysis or investment analytics
• Prior experience within investment management, financial services, or firms that serve them (hedge funds, asset managers, fintech, financial consulting)
• Proficiency in Python and advanced SQL for both data engineering and analytical work
• Experience with modern data platforms (Snowflake, Databricks, or similar) and data modeling principles
• Demonstrated ability to communicate technical concepts to non-technical investment professionals
• Comfort working directly with senior clients and managing stakeholder expectations

Qualifications

• Required: 5+ years of hands-on experience in a role that combined data/analytics engineering with business analysis or investment analytics
• Required: Prior experience within investment management, financial services, or firms that serve them (hedge funds, asset managers, fintech, financial consulting)
• Required: Proficiency in Python and advanced SQL for both data engineering and analytical work
• Required: Experience with modern data platforms (Snowflake, Databricks, or similar) and data modeling principles
• Valued: Demonstrated ability to communicate technical concepts to non-technical investment professionals
• Valued: Comfort working directly with senior clients and managing stakeholder expectations

Benefits

This role offers a path to join a leading Bay Area-based asset allocator, with an anticipated transition by January 2027.