Torchora
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Key Responsibilities and Required Skills for Finance Data Analyst

💰 $75,000 - $115,000

FinanceData & AnalyticsBusiness Intelligence

🎯 Role Definition

As a Finance Data Analyst, you will serve as a critical bridge between our vast financial data resources and strategic business initiatives. You are not just a number cruncher; you are a storyteller, an investigator, and a strategic partner. You will dive deep into financial datasets to identify trends, build predictive models, and create compelling visualizations and reports that empower our finance and executive leadership. This role is perfect for a curious and driven individual who thrives on solving complex problems and wants to make a tangible impact on the company's financial health and growth trajectory.

📈 Career Progression

Typical Career Path

Entry Point From:

  • Financial Analyst
  • Business Analyst
  • Junior Data Analyst
  • Staff Accountant

Advancement To:

  • Senior Finance Data Analyst
  • Finance Manager / FP&A Manager
  • Business Intelligence Manager
  • Data Science Manager

Lateral Moves:

  • Data Scientist
  • Business Intelligence Developer
  • Corporate Strategy Analyst
  • Product Analyst

Core Responsibilities

Primary Functions

  • Develop, maintain, and enhance complex financial models for forecasting, budgeting, and long-range planning to support strategic decision-making.
  • Conduct in-depth variance analysis, comparing actual financial performance against budgets and forecasts, and providing clear, actionable commentary on key drivers.
  • Design, build, and automate interactive dashboards and reports in BI tools like Tableau or Power BI to visualize financial KPIs and business performance metrics for leadership.
  • Extract, transform, and analyze large, complex financial datasets from multiple sources (ERP, CRM, data warehouses) using advanced SQL queries.
  • Partner with the Finance and Accounting teams to support month-end, quarter-end, and year-end closing processes through data validation and reporting.
  • Analyze and report on key business drivers, including revenue trends, customer acquisition costs (CAC), lifetime value (LTV), and product profitability.
  • Perform deep-dive analyses into operating expenses and cost structures to identify opportunities for cost savings and efficiency improvements.
  • Collaborate with business stakeholders to understand their challenges, and then formulate and answer critical questions using data-driven insights.
  • Develop and implement statistical models and algorithms to generate forward-looking insights and predict future financial performance.
  • Automate manual data collection, aggregation, and reporting processes using Python, SQL, and BI tools to improve team efficiency and accuracy.
  • Prepare and deliver compelling presentations that summarize analytical findings and provide strategic recommendations to senior management and executive teams.
  • Ensure the integrity, accuracy, and timeliness of all financial data by establishing and overseeing robust data validation processes.
  • Support the annual operating plan (AOP) and quarterly forecast cycles by providing data-driven inputs and scenario modeling.
  • Analyze the financial impact of potential business decisions, such as new product launches, pricing changes, and capital investments.
  • Create and maintain a centralized repository of key financial metrics and definitions to ensure consistency in reporting across the organization.
  • Monitor financial trends and industry benchmarks to provide context for company performance and identify potential risks and opportunities.
  • Collaborate with the Data Engineering team to define data requirements and assist in the development of data pipelines for financial reporting.
  • Evaluate and recommend new tools and technologies to enhance the capabilities of the finance analytics function.
  • Drive the enhancement of financial reporting systems and processes to support the company's growth and evolving needs.
  • Conduct ad-hoc financial analysis and projects as requested by leadership to support time-sensitive, strategic initiatives.
  • Mentor junior analysts and champion a data-driven culture within the finance organization.

Secondary Functions

  • Support ad-hoc data requests and exploratory data analysis from various business units.
  • Contribute to the organization's data governance and data strategy initiatives.
  • Collaborate with business units to translate data needs into engineering requirements.
  • Create and maintain comprehensive documentation for data models, metrics, and reporting logic.
  • Participate in sprint planning and agile ceremonies within the data and analytics team.

Required Skills & Competencies

Hard Skills (Technical)

  • Advanced proficiency in SQL for querying and manipulating large, complex datasets from relational databases and data warehouses.
  • Expert-level skills in Microsoft Excel, including pivot tables, advanced formulas, Power Query, and building sophisticated financial models.
  • Strong experience with data visualization and Business Intelligence tools such as Tableau, Power BI, Looker, or Qlik.
  • Proficiency in a scripting language for data analysis, preferably Python (with libraries like Pandas, NumPy, Matplotlib) or R.
  • Solid understanding of financial principles, accounting concepts (GAAP), and financial statements (P&L, Balance Sheet, Cash Flow).
  • Experience with Enterprise Resource Planning (ERP) systems (e.g., SAP, Oracle NetSuite, Microsoft Dynamics) and retrieving data from financial modules.
  • Knowledge of statistical analysis and techniques for predictive modeling, regression, and trend analysis.
  • Familiarity with data warehousing concepts (e.g., Snowflake, BigQuery, Redshift) and ETL (Extract, Transform, Load) processes.
  • Demonstrated ability in building and maintaining complex financial models for budgeting, forecasting, and what-if scenario analysis.
  • Experience with financial planning and analysis (FP&A) software like Anaplan, Adaptive Insights, or Oracle Hyperion is a significant plus.

Soft Skills

  • Exceptional analytical and quantitative problem-solving skills with a keen attention to the smallest details and a commitment to accuracy.
  • Superior communication and presentation skills, with the ability to translate complex data into a clear and compelling narrative for non-technical audiences.
  • High degree of business acumen and the ability to understand how data insights connect to and impact broader business outcomes.
  • Proactive and intellectually curious mindset, with a genuine passion for asking "why" and uncovering insights hidden beneath the surface.
  • Strong organizational and time-management skills to effectively manage multiple projects and ad-hoc requests in a fast-paced environment.
  • Collaborative team player with excellent interpersonal skills to build relationships and work effectively across different departments and levels of the organization.

Education & Experience

Educational Background

Minimum Education:

  • Bachelor's Degree

Preferred Education:

  • Master's Degree (e.g., MS in Finance, Analytics, Data Science, or MBA)

Relevant Fields of Study:

  • Finance
  • Economics
  • Accounting
  • Statistics
  • Data Science or Analytics
  • Computer Science

Experience Requirements

Typical Experience Range:

  • 2-5 years of professional experience in a financial analysis, data analysis, FP&A, or business intelligence role.

Preferred:

  • Experience within the tech, SaaS, FinTech, or e-commerce industries is highly desirable.
  • Proven experience working directly with large-scale datasets and cloud data platforms (e.g., Snowflake, AWS Redshift, Google BigQuery).
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