Senior Data Analyst, Financial Analytics

About the role

You will serve as a primary analytical resource for executive leadership. You will translate complex financial and operational data into clear, decision-grade analysis that drives how the organization understands its revenue trajectory, manages intra-quarter performance, and sets expectations with its most senior stakeholders.

Responsibilities

• Support forecasting of Rocket’s mortgage production & revenue across all channels, contributing analytical work across long-range forecasts, quarterly outlooks, and regular updates that reflect the latest business trends and macroeconomic conditions.
• Own intra-quarter pacing analysis, monitoring revenue and EPS performance relative to targets throughout the quarter, identifying risks and opportunities early, and providing actionable insight to finance leadership on how to close gaps or capitalize on upside.
• Identify and execute opportunities to automate existing financial reporting processes, reducing manual effort and improving consistency and reliability of recurring deliverables.
• Build and maintain enterprise-level P&L models, including active development of a loan-level P&L integrated with Snowflake.
• Develop and maintain production goal-setting models for sales, translating financial targets into associated operational goals.
• Support quarterly earnings preparation by providing data, trend analysis, and analytical context to the Investor Relations (IR) team; partner with IR and finance leadership to help shape the narrative for prepared remarks based on observed business performance.
• Partner with engineering to integrate finance source systems into Snowflake and establish a scalable, finance-owned data foundation.
• Create and maintain reporting tools, dashboards, and automated data pipelines in Power BI, SQL, and Excel that serve both recurring reporting needs and ad hoc analytical requests.
• Proactively surface trends, anomalies, and business opportunities through data analysis, and bring findings to finance and executive leadership with clear recommendations.
• Define, validate, and document data requirements and quality standards for finance data sources.
• Contribute to the buildout of finance data infrastructure on Snowflake, including integration of AI-assisted workflows to streamline financial analysis and reporting.

Requirements

• Bachelor’s degree or equivalent experience in a scientific discipline, mathematics, applied statistics, information technology, or a related field.
• 4+ years of experience in data analysis, financial analysis, or a closely related discipline, with demonstrated impact on business decisions.
• Advanced SQL proficiency; experience building and maintaining complex queries against enterprise data warehouses.
• Strong working knowledge of Power BI or comparable BI platforms, with experience developing production-grade dashboards and reports.
• Advanced Excel skills, including financial modeling, scenario analysis, and large dataset handling.
• Experience with Python, R, or comparable scripting tools for data manipulation and analysis.
• Demonstrated ability to communicate analytical findings clearly to senior, non-technical stakeholders — including written narrative, verbal presentation, and data visualization.
• Experience producing forecasts or performance analysis consumed by C-suite or senior executive audiences.
• Experience in financial reporting, revenue analysis, forecasting, P&L construction, or a comparably rigorous quantitative discipline.
• Strong judgment in balancing speed and accuracy when operating under reporting deadlines.

Preferred Qualifications

• Experience working with or transitioning data to cloud platforms such as Snowflake, Azure, or similar.
• Familiarity with mortgage banking, consumer lending, or financial services data and business models.
• Experience designing or contributing to data warehouse schemas for finance or accounting use cases.
• Exposure to capital markets, fixed income, or loan-level financial analysis.
• Experience with AI-assisted tooling or workflow automation in an analytical or finance context.
• Experience supporting earnings preparation or working alongside an Investor Relations function.
• Experience mentoring analysts or contributing to team standards and documentation.