Sr. Real Estate Financial Data Analyst

Investment Real Estate•York, PA

3d•Onsite

About The Position

The Senior Real Estate Financial Data Analyst will lead business intelligence, analytics, reporting, and decision-support for a growing self-storage and real estate organization. Reporting to the Chief Financial Officer, this hands-on role transforms financial, operational, customer, and market data into actionable insights that improve revenue, occupancy, budgeting, forecasting, customer service, and portfolio performance. The successful candidate will be highly organized, detail-oriented, and able to connect analysis to the broader business strategy. They will be proactive, resourceful, and comfortable working independently in a fast-paced environment. A customer-service focus and responsiveness to the needs of executives, corporate teams, and field operations are essential. The role requires a practical problem solver who communicates complex findings clearly to non-technical stakeholders, and who is collaborative, adaptable, accountable, and willing to work on-site in York, Pennsylvania.

Requirements

Bachelor’s degree in data analytics, data science, statistics, mathematics, computer science, finance, accounting, economics, business, or a related field.
Five or more years of progressively responsible experience in business intelligence, analytics, financial analysis, data science, or a comparable role.
Expert-level Power BI experience, including dashboard design, DAX, Power Query, data modeling, visualization, administration, and automated reporting.
Advanced Excel skills; working knowledge of SQL, relational databases, and integration of data from multiple platforms.
Experience with API development or integration.
Excellent analytical judgment, written and verbal communication, project management, organization, accuracy, and ability to perform under changing priorities.
Ability and willingness to work on-site in York, Pennsylvania.

Nice To Haves

Self-storage experience strongly preferred, including property operations, budgeting, revenue management, pricing, occupancy, and multi-location performance analysis.
Python, R, Microsoft Fabric, Azure, data warehouses, machine learning, or AI tools are additional advantages.
Experience with Sage 100, AvidXchange, Self Storage Manager or comparable property-management software, and Veritec or comparable revenue-management technology is a plus.

Responsibilities

Serve as the company’s Power BI subject-matter expert; design, develop, deploy, and maintain executive, financial, operational, revenue-management, marketing, and property-level dashboards.
Build scalable data models using Power Query, DAX, semantic modeling, automated refreshes, permissions, documentation, and quality controls.
Replace manual spreadsheet reporting with accurate, repeatable, user-friendly reporting solutions and train employees to interpret and use the information.
Analyze occupancy, economic occupancy, move-ins, move-outs, achieved and street rates, discounts, concessions, delinquency, retention, lead conversion, and unit-type performance.
Partner with operations and revenue management to evaluate pricing, rate increases, promotions, demand patterns, customer behavior, competitive conditions, and underperforming properties.
Measure the impact of operational, marketing, pricing, and customer-service initiatives and identify opportunities to improve revenue, occupancy, retention, and net operating income.
Support annual property and portfolio budgets, monthly forecasting, variance analysis, scenario planning, and performance comparisons to budget, prior year, forecast, and underwriting.
Analyze revenue, operating expenses, NOI, capital expenditures, and other financial measures; clearly explain significant variances and business implications.
Assist with acquisition underwriting, due diligence, post-closing performance tracking, and integration reporting as requested.
Develop statistical, predictive, machine-learning, or AI-supported models when appropriate for revenue forecasting, pricing optimization, customer retention, lead conversion, and property performance.
Develop, maintain, or support APIs and other integrations among operational, accounting, accounts-payable, revenue-management, and reporting platforms.
Create reliable data pipelines and automated workflows that consolidate information, reduce duplicate entry, and eliminate unnecessary manual processes.
Evaluate emerging analytical and AI technologies based on business value, scalability, cost, security, and user adoption.
Establish consistent KPI definitions, reconcile outputs to source systems and accounting records, troubleshoot discrepancies, and maintain documentation of data sources and methodologies.
Protect confidential company, customer, employee, and financial information and support sound data-governance practices.
Translate business questions into practical analytical solutions, manage competing priorities, and provide responsive service to internal customers and third-party technology partners.