Data Analyst

MLG Capital•Goerke's Corners, WI

About The Position

About MLG Capital MLG Capital is a private real estate investment manager focused on delivering long-term, tax-efficient, risk-adjusted returns through diversified real estate strategies across the United States. As our platform continues to scale nationally, we are strengthening our data and reporting capabilities to drive operational efficiency, improve decision-making, and reduce the time required to produce core business insights. This is MLG’s first-ever Data Analyst hire, supporting the modernization of reporting, analytics, and data operations across the firm. Role Overview This position will serve multiple business lines, working closely with Asset Management, Portfolio Management, Acquisitions teams and more over time, to ensure that data-driven efficiencies are introduced wherever they are most needed. By collaborating across these areas, the Data Analyst will help deliver timely, accurate insights and empower each team to make more informed decisions and achieve their goals with greater speed, while working with the Data Engineering team and BI team to continue to deliver automated and scalable solutions. The analyst will act as the data and process subject matter expert for these business lines, helping ensure our asset-level and portfolio-level data is complete, clean, and ready for faster reporting with reduced manual effort.

Requirements

2–5 years of experience as a Data Analyst or Reporting Analyst; real estate or financial services experience highly recommended.
Expert Excel skills and very strong with BI/reporting tools (Power BI preferred).
Ability to work with messy or incomplete data and improve it through cleansing and transformation.
Understanding of data modeling basics and data process flows.
Strong verbal and written communication skills, including translating business needs into data requirements.
Process-oriented mindset with passion for increasing efficiency and reducing manual work.
Comfortable working with both business stakeholders and technical teams.
Innate curiosity and critical thinking skills; thrives on solving complex problems and enjoys the challenge of unraveling data puzzles to uncover valuable insights.
Skilled at bridging the gap between technical and business perspectives, able to communicate effectively across teams and tailor solutions to meet real-world needs.
Self-motivated and energized by challenges; approaches obstacles as opportunities for creative solutions and continuous improvement.
Team-oriented mindset; values collaboration, celebrates collective wins, and contributes to a positive, high-performance culture.

Nice To Haves

real estate or financial services experience highly recommended.
Power BI preferred

Responsibilities

Act as the subject matter expert for data, workflows, KPIs, and reporting logic across Asset Management, Portfolio Management, Fund Accounting/Tax, and Acquisitions.
Proactively engage business stakeholders—including senior leadership—to gather, document, and align reporting requirements, data sources, and field definitions with organizational goals.
Partner with BI Developers and Data Engineering to deliver scalable, automated reporting solutions, resolve data gaps, and improve pipeline robustness.
Maintain and refresh recurring weekly, monthly, and quarterly reports, dashboards, and Excel/BI outputs for business consumption.
Clean, transform, and standardize data, ensuring quality through QA, reconciliation, exception detection, and report testing.
Implement data quality frameworks, validation rules, and monitoring processes to ensure analytics outputs are accurate, reliable, and consistent.
Establish and manage structured project workflows, cross-functional collaboration, and effective communication across assigned initiatives.
Continuously review and enhance reporting workflows, data intake, and operational procedures to identify and eliminate inefficiencies and bottlenecks.
Map and recommend improvements for current- and future-state workflows to increase scalability, reduce manual effort, and promote operational excellence.
Document business logic, field definitions, DDL, KPI formulas, and reporting requirements to support knowledge sharing and process transparency.
Support change-management efforts to drive adoption and maintenance of new and enhanced data solutions.
Advocate for standardized data practices and collaborate on initiatives to enhance data completeness, accuracy, and auditability.
Identify gaps in data feeds and scope new sources to advance analytics capabilities.
Recommend and implement enhancements that support the firm's strategic goals for data-driven decision-making.