Financial Data Analyst

Company Overview

Austin Capital Bank is a fast‑growing, tech‑forward community bank based in Austin, Texas. We’re a nationwide leader responsible financial innovation—combining the stability of a 500 million‑dollar regulated bank with the agility of a fintech. Our mission is to deliver simple reliable, and customer‑friendly financial products that improve the financial well‑being of people across the country. Our products have touched over a million customers in all 50 states.

• A supportive team culture with approachable leaders and good snacks.
• A profitable and growing business with strong financials.
• Opportunities to grow through career development, tuition assistance, and cross‑functional roles.
• Full‑coverage employer‑paid medical, dental, and vision insurance.
• Wellness program with extra funds for out‑of‑pocket medical expenses.
• Generous paid time off—16 days per year that grows with tenure.
• Paid holidays—11+ per year.
• 401(k) with 4% employer match.

• Wicked Smart – Intellectually and emotionally self‑aware.
• Take Initiative – Bias to action and forward momentum.
• No Big Egos – Self‑confidence with humility.
• Honesty – Respectful and direct forthright communication.
• Curiosity – Innovation that goes beyond the line.

Austin Capital Bank (ACB) is hiring a Financial Data Analyst to align our financial forecasting and reporting with the Data Analytics organization. You will own the data structures, models, and analyses that power financial planning and forecasting, partner closely with Finance during monthly/quarterly close, and deliver high‑quality insights to business and product leaders.

• Build and maintain driver‑based financial models to support annual operating plans and rolling forecasts.
• Perform monthly variance analysis (Actuals vs. Budget/Forecast) and partner with Finance and the data team to explain movements and recommend corrective actions.
• Create scenario/sensitivity analyses for revenue, unit economics, and margin outcomes; quantify risks and opportunities.
• Support month‑end and quarter‑end close with reconciliations, accruals, and cohort/deferral schedules; ensure alignment between finance reports and source data.
• Develop standardized KPI packages and executive dashboards (e.g., revenue, contribution margin, CAC/LTV, churn/retention, cohort profitability, cash runway). Refresh on a predictable cadence.

• Write high‑quality SQL to extract, join, transform data from our cloud data warehouse; curate reliable, documented datasets for Finance and Accounting.
• Collaborate with analytics engineering (e.g., dbt) to product ionize finance models and ensure version control, testing, and lineage.
• Build automated data quality checks and partner with Finance to resolve exceptions.
• Optimize query performance and data partitioning for timely reporting across month‑end close and weekly forecast cycles.
• Partner with fraud and product teams to incorporate key drivers (pricing, interchange, charge‑offs, fraud losses, partner fees) into finance datasets.

• Translate complex data findings into concise narratives, visuals, and clear recommendations for Finance and Executive Team.
• Establish SLAs for recurring deliverables (close packages, board metrics, forecast refreshes) and communicate deviations proactively.
• Document assumptions, definitions, and metric logic; drive alignment on a single source of truth for financial KPIs.

• 3–6 years in FP&A, financial analysis, or data analytics supporting finance within fintech, banking, SaaS, or similar data‑rich domains.
• Intermediate SQL with demonstrated experience querying large datasets in a cloud data warehouse (e.g., Snowflake, Big Query, Redshift).
• Strong proficiency in Excel/Sheets (index/match/xlookup, nested logic, pivoting, scenario/sensitivity modeling).
• Solid understanding of financial statements (P&L, balance sheet, cash flow), GAAP concepts (revenue recognition, accruals, deferrals), and variance analysis.
• Experience building driver‑based forecast models and operational KPI dashboards for executive…