Financial Data Analyst

Financial Data Analyst
Full-Time | Austin Capital Bank | Austin, TX

Company Overview
Austin Capital Bank is a fast-growing, tech-forward community bank based in Austin, Texas. We’re a nationwide leader in 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.
We’ve been recognized on the Inc. 5000 list of fastest-growing companies multiple years in a row—and we’re just getting started. Our team members are approachable, attentive, and trusted problem-solvers who take pride in doing right by our customers and each other.

Why You’ll Love Working Here

• A team that feels like a team – Supportive coworkers, approachable leaders, and a culture that values listening, learning, collaboration…and good snacks
• It feels great to contribute to a company that’s winning and growing – our financials say it all – we’re nicely profitable and gaining market share.
• Opportunities to grow – Career development, tuition assistance, and room to explore roles across the bank.
• 100% Employer-paid medical, dental, & vision insurance – Full coverage for employee-only plans, with affordable family options.
• Wellness program – Extra funds from us to help cover your out-of-pocket medical expenses.
• Generous paid time off – Start with 16 days per year that grows with tenure.
• Paid holidays – 11+ per year, so you can truly unplug.
• 401(k) with 4% employer match – Invest in your future with our support.

Our Core Values
At Austin Capital Bank, every team member embodies our values. We work, hire, promote, and lead by them:

• Wicked Smart – Intellectually and emotionally self-aware.
• Take Initiative – A bias to action, movement forward.
• No Big Egos – Self-confidence with humility.
• Honesty – Respectful and direct forthright communication.
• Curiosity – Innovation doesn’t come from drawing within the lines.

If you’re someone who rolls up their sleeves, leads with integrity, and believes that kindness and high performance can coexist, you’ll fit right in.

About The Role
Austin Capital Bank (ACB) is hiring a Financial Data Analyst to align our financial forecasting and reporting with 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. The ideal candidate combines strong finance acumen (budgeting/forecasting/variance analysis) with hands-on data skills (SQL, cloud data warehouses, and modern analytics tools).

What You’ll Do
Finance Planning, Forecasting & Reporting

• Build and maintain driver-based financial models to support annual operating plans and rolling forecasts (revenue, COGS, Opex, headcount, capex).
• Perform monthly variance analysis (Actuals vs. Budget/Forecast) and partner with Finance and the data team to explain movements, uncover drivers, and recommend corrective actions.
• Create scenario/sensitivity analyses (best/base/worst cases) 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), refreshing on a predictable cadence.

Data Analytics

• Write or generate high-quality SQL to extract, join, and transform data from our cloud data warehouse; curate reliable, documented datasets for Finance and Accounting.
• Collaborate with analytics engineering (e.g., dbt) to productionize finance models and ensure version control, testing, and lineage.
• Build automated data quality checks (reconciliation rules, threshold monitors) 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.

Stakeholder Enablement & Communication

• Translate complex data findings into concise narratives, visuals, and clear recommendations for Finance and the 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.

What You Bring
Required

• 3–6 years in FP&A, financial analysis, or data analytics supporting finance within fintech, banking, SaaS, or similarly data-rich domains.
• Intermediate SQL with demonstrated experience querying large datasets in a cloud data warehouse (e.g., Snowflake, BigQuery, 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 audiences.
• Clear, concise communication skills; ability to translate technical details into business insights.

Preferred

• Experience with dbt and modular analytics modeling; familiarity with CI/testing and documentation practices.
• Python (pandas, numpy) or R for analysis, reconciliation, or statistical analysis.
• Familiarity with BI/analytics tools (ThoughtSpot, Looker, Tableau, Power BI) including data modeling and governance.
• Exposure to banking/fintech economics: interchange, ACH, BIN sponsorship, fraud losses, charge-offs, loss provisioning, and cohort/retention analysis.
• Experience designing metric definitions and data contracts that align Finance with Product, Risk, and Operations.
• Hands-on use of AI prompts/agents for data tasks, with evidence of rigorous validation and controls.

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