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# Performance Engineer - Performance Analytics

- **Company:** TIAA
- **Location:** New York, NY, United States
- **Experience:** Experienced
- **Salary:** $160,000.0 - $180,400.0
- **Contract:** Permanent contract
- **Skills:** Information Engineering, Data Visualization, Python (Programming Language), SQL Databases, Information Technology, Performance Monitor
- **Published:** September 3, 2026
- **Apply:** https://www.dice.com/job-detail/4e70c57f-1c93-495d-b082-10845583a8a0

## About the Role

* University (Degree) Preferred, * Minimum of 3+ years of experience in investment analytics, portfolio accounting, or data engineering/analytics.
 * Proficiency in both Python and SQL.
 * Strong analytical and problem-solving skills with exceptional attention to detail.
 * Comfortable working in fast-moving, high-accountability environments where accuracy and speed both matter., * 5 years of experience in investment analytics, portfolio accounting, or data engineering/analytics.
 * Bachelor's or Master's degree in Finance, Accounting, Mathematics, Computer Science, or a related quantitative field.
 * Solid understanding of investment performance concepts, including returns, benchmarks, attribution, and reconciliation.
 * Experience with data visualization or workflow automation tools is a plus.

## Description

The Performance Engineer role on our Brooklyn team helps ensure the accuracy, consistency, and explain ability of portfolio performance across our platform.

Our platform was designed to support millions of accounts across custom benchmarks and multi-sleeve portfolio structures. The systems that power these are sophisticated and deeply integrated into daily after-tax reporting and trading. This role is ideal for someone who enjoys working at the intersection of data, finance, and scalable systems, and who takes satisfaction in getting to the bottom of numerical discrepancies others can't explain.

You'll work closely with our quant and engineering teams to analyze differences between modeled and actual portfolio returns, and conduct performance attribution - helping to identify root causes, validate fixes, and strengthen the robustness of our performance analytics., * Investigate and reconcile account-level and benchmark performance data across internal models, benchmark systems, and custodian data.

 * Analyze benchmark definitions, blending logic, and drifted allocations to ensure consistency with expected outcomes.
 * Build diagnostic scripts in Python and structured queries in SQL to isolate and document root causes of deviations.
 * Collaborate with engineers to translate findings into long-term system updates and validation rules.
 * Develop and maintain data-quality dashboards, audit trails, and investigative documentation.
 * Partner with portfolio management, operations, and engineering teams to improve transparency and trust in performance reporting.


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