Sr. Portfolio Data Analyst

San Mateo, CA

The Sr. Portfolio Data Analyst serves as the senior data authority for Portfolio Management within the Platform Business organization. This role designs and delivers scalable data solutions and advanced analytics to provide real-time, trusted insights into portfolio performance, enabling data-driven investment and prioritization decisions. The position combines deep financial acumen, technical expertise, and portfolio evaluation to guide strategic outcomes.

Key Responsibilities

• Architect and maintain scalable data pipelines integrating program, financial, and operational data into a unified portfolio data model.
• Develop executive-ready dashboards and analytics (KPIs, trends, forecasts) to assess portfolio health, performance, ROI, and value realization.
• Lead portfolio reporting (operational and quarterly), including budget vs. actuals, forecasting, resource capacity, and delivery metrics.
• Perform advanced financial and scenario modeling to evaluate trade-offs, risks, and investment outcomes across the portfolio.
• Ensure data integrity through validation, governance, and standardized definitions; document data lineage and business rules.
• Automate reporting and analytics workflows to improve efficiency and scalability.
• Partner with Finance, Program Delivery, and Strategy teams to align portfolio metrics with ROI frameworks and business outcomes.
• Support executive decision-making with clear, actionable insights and portfolio performance narratives.
• Mentor analysts and promote best practices in analytics, data modeling, and visualization.

Qualifications

• Bachelor’s degree in Business Analytics, Finance, Computer Science, or related field; advanced degree a plus. 
• 6–8 years of experience in portfolio management, finance, or strategy within a technology-driven environment.
• Strong expertise in financial modeling, ROI analysis, forecasting, and portfolio performance assessment.
• Proven ability to evaluate portfolio health (capacity, risk, dependencies, and outcomes).
• Advanced technical skills: SQL and Python/R; experience building data pipelines and analytical models.
• Proficiency in BI tools (Tableau, Power BI) and Excel for executive-level reporting.
• Experience with data governance, system integration, and large-scale data validation.
• Strong cross-functional collaboration and ability to translate complex data into strategic insights.