Senior Data Analyst

Key Responsibilities

• Extract, transform, and normalize performance data from systems such as Yardi, Salesforce, and internal databases using SQL, Databricks, and automated ETL processes.


• Calculate, validate, and analyze investment performance metrics (IRR, MOIC, DPI, RVPI, TWR, GAV/NAV) at property, investment, and fund levels.


• Support track record construction, return aggregation, variance analysis, and reconciliation of calculated results to source systems.


• Build and maintain Excel models, templates, and dashboards using tools such as Power BI, Tableau, or Domo.


• Execute data quality checks, reconciliations, and governance processes; document sources, logic, and business rules in partnership with the Data Steward.


• Prepare benchmark and investor reporting inputs, including NCREIF/MSCI submissions, partner reports, DDQs, capital accounts, and ILPA-compliant deliverables.


• Support quarterly and annual close activities by validating performance data used in financial and investor reporting.


• Assist with data modernization initiatives, platform migrations, UAT testing, and process automation efforts.


• Collaborate cross-functionally with Investments, Finance, Operations, Data Engineering, and external vendors to meet reporting and analytics needs.

Education & Experience

• Bachelor's degree in Finance, Accounting, Economics, Data Analytics, Information Systems, or related field.


• 2-4 years of experience in data analysis, financial reporting, investment operations, or fund administration (internship experience considered).


• Exposure to private equity, real estate, or alternative investments preferred.


• Interest in or progress toward CFA, CAIA, or CPA a plus.

Technical & Core Skills

• Advanced Excel skills (Power Query, pivot tables, complex formulas).


• Strong SQL querying experience; familiarity with Databricks or modern data platforms preferred.


• Experience with data visualization tools (Power BI, Tableau, Domo).


• Strong analytical, organizational, and communication skills; high attention to data accuracy and confidentiality.


• Ability to manage multiple priorities and communicate insights to non-technical stakeholders.


• Interest in investment performance, data governance, and emerging technologies, including AI tools.