Senior Associate, Data Governance

Location Designation:Hybrid - 4 days per week

As a top 25 global asset management firm with more than $700 billion in assets under management, we have an important mission: to help build a better financial future for our clients, our employees, and our communities. We invite you to bring your talents to New York Life Investments, so we can continue to help people achieve their financial aspirations.

With over 100 years in business, New York Life Real Estate Investors (NYL REI) is a division of NYL Investors LLC, a wholly owned subsidiary of New York Life Insurance Company. NYL REI manages over $70 billion in real estate‑related assets including commercial mortgage loans, CMBS, and direct real estate equity investments on behalf of New York Life’s general account and third‑party institutional investors.

The Data Governance Senior Associate will play a critical role in strengthening the accuracy, consistency, and transparency of data used across NYL REI’s real‑estate investment platform. This includes supporting data needs across equity investments, commercial mortgage lending, asset management, portfolio management, operations, and reporting. The Senior Associate ensures that data across all real‑estate asset types is complete, comparable, and aligned with internal standards.

• Support the implementation of NYL REI’s data governance framework.
• Maintain and enhance the data dictionary for property, tenant, lease, loan, valuation, and performance data.
• Promote consistent use of data standards, definitions, and business rules across all real‑estate teams.
• Build and monitor data quality rules and KPIs (e.g., completeness, accuracy, timeliness, consistency).
• Proactively identify and investigate data issues, including rent roll discrepancies, valuation mismatches, or new loan onboarding issues.
• Partner with system owners and business teams to resolve root causes and improve upstream data processes.
• Validate operational and financial data in collaboration with asset management, portfolio management, and accounting teams.
• Ensure proper documentation, testing standards, and data controls are followed.

• Support metadata management activities and contribute to the use of modern cataloging and governance platforms.
• Help define, implement, and enforce data lineage standards across cloud BI and analytics environments.
• Establish cross‑system lineage connections across Dealpath, Yardi, PLM, Built, Loan Manager, valuation platforms, and reporting solutions.
• Contribute to standardized naming conventions, documentation requirements, and transformation testing.
• Prepare materials and support governance councils, working groups, and executive forums.
• Contribute to governance procedures, training materials, and the adoption of data ownership and stewardship practices.
• Support SharePoint and document governance processes, including version control and document‑level metadata.
• Participate in evaluating and implementing modern data quality and observability frameworks (e.g., anomaly detection, rule‑based validation tools).
• Assist in governance workflows embedded within modern data transformation frameworks.
• Apply an understanding of the real‑estate data lifecycle — including deal intake, underwriting, operations, accounting, loan management, and investor reporting — to support modernization efforts.
• Collaborate with BI, engineering, and enterprise data teams to align real‑estate governance practices with cloud, data, and AI modernization initiatives.

• Bachelor’s degree required, preferably in real‑estate, finance, economics, accounting, information systems, or a related investments or data discipline.
• 5+ years of experience in data governance, data management, or analytics, ideally within real‑estate.
• Familiarity with real‑estate systems and BI tools (Yardi, Precision LM, Dealpath, Qlik).
• Exposure to modern governance concepts including data catalogs, metadata management, observability, and lineage.
• Understanding of cloud data and modern data stack practices such as data quality rules, transformation testing,…