Senior Finance Data Analyst

About the Role

The Senior Finance Data Analyst is responsible for collecting, analyzing, and interpreting financial and operational data to help the business make informed decisions. The role involves preparing financial reports, identifying trends and issues, ensuring data accuracy, and providing recommendations to improve business performance.

The analyst will work closely with Finance, Operations, Account Management, and senior leaders to explain financial results and present practical, data-driven recommendations.

Key Responsibilities1. Financial Data Analysis and Reporting

• Collect, organize, and analyze financial and operational data from different systems.
• Monitor revenue, expenses, profit margins, labor costs, productivity, and client profitability.
• Prepare monthly, quarterly, and special financial reports.
• Compare actual results against budgets, forecasts, and previous periods.
• Support budgeting, forecasting, and financial planning.
• Measure business performance using financial and operational data.

2. Data Analysis and Business Insights

• Investigate changes in financial results and identify their root causes.
• Analyze trends and patterns to help the business make better decisions.
• Monitor key performance indicators (KPIs) and identify potential risks and opportunities.
• Explain how operational factors, such as staffing, productivity, and working hours, affect financial performance.
• Provide recommendations based on data analysis.

3. Data Accuracy and Quality Control

• Check financial reports against original records and source systems.
• Identify and correct data errors, inconsistencies, and missing information.
• Create data validation checks to ensure reports are accurate and reliable.
• Maintain proper documentation and audit records.
• Work with Finance and Operations to prevent recurring data issues.

4. Reporting and Presentations

• Prepare clear financial reports, dashboards, and executive summaries.
• Present findings to senior management, business leaders, and clients.
• Explain complex data in a simple and understandable way.
• Recommend practical improvements and explain their expected financial impact.
• Monitor the results of implemented recommendations.

5. Collaboration and Team Support

• Work with data engineering teams to ensure reliable data systems and reporting processes.
• Organize and maintain databases and reusable data structures.
• Guide junior analysts in financial analysis, documentation, and report preparation.
• Use AI tools, such as Claude, to improve analysis, documentation, and quality checks while ensuring the accuracy of the results.

Qualifications and SkillsTechnical Skills

• Advanced Excel skills, including financial modeling, pivot tables, lookups, and handling large datasets.
• Strong SQL skills, including complex queries, joins, aggregations, and window functions.
• Experience using Python for data analysis, automation, and data manipulation.
• Knowledge of data visualization tools such as Power BI and Tableau.
• Understanding of statistics and analytical methods.
• Familiarity with cloud data warehouses, preferably Snowflake, and data transformation tools such as dbt is an advantage.

Financial and Business Knowledge

• Strong understanding of financial statements, revenue, expenses, profit margins, budgeting, and forecasting.
• Ability to connect operational performance with financial results.
• Good business judgment and the ability to prioritize analysis that supports decision-making.

Core Competencies

• Strong analytical, mathematical, and problem-solving skills.
• Excellent attention to detail and commitment to data accuracy.
• Ability to investigate problems and identify their root causes.
• Strong written and verbal communication skills in English.
• Ability to present findings clearly to senior leaders and clients.
• Good teamwork and stakeholder management skills.
• Integrity and discretion when handling confidential financial information.

Experience

• At least 5 years of experience in data analysis, including significant experience working with financial data.
• Proven experience in financial reporting, variance analysis, cost analysis, or profitability analysis.
• Experience presenting findings and recommendations to senior management, executives, or clients.
• Experience with financial data reconciliation, audits, and reporting controls.
• A bachelor's degree in Finance, Accounting, Economics, Business Analytics, Statistics, Engineering, or a related field.
• Professional certifications such as CPA, CFA, or FP&A are an advantage.