Finance Data Steward & Analyst

About Xtend_Ops

XtendOps combines leading-edge cloud-based technologies with a world-class managed workforce solution. We’re a modern offshoring entity built around amazing people and innovative digital solutions. Agile and adaptable, we quickly respond to evolving client needs and work closely with our clients to design customized outsourcing strategies that improve operations, customer experience, and business performance.

Job Overview

The Finance Data Steward & Analyst is responsible for managing and maintaining accurate financial data across the company's data warehouse and operational systems. The role ensures that financial metrics, such as revenue, payroll costs, invoicing, and profit margins, are clearly defined, properly documented, and reconciled with their original sources.

The analyst will work closely with Finance, Operations, and Data Engineering to connect financial data with operational performance, identify discrepancies, monitor account profitability, and provide recommendations that support business decisions. The role also involves using AI tools, such as Claude, to assist with SQL queries, data models, and documentation.

Key Responsibilities

1. Financial Data Management

• Define and document financial metrics, including revenue, billable hours, labor costs, cost of delivery, gross margin, and cost per productive hour.
• Maintain data tables that connect clients, accounts, programs, cost centers, and payroll entities across different systems.
• Coordinate with payroll providers, Finance, and Billing teams to establish data requirements, update schedules, and validation rules.
• Establish access controls for payroll data to protect confidential employee information.
• Maintain the methodology used to allocate shared-services costs.
• Use AI tools to help develop SQL queries, dbt models, and data tests, and validate the results against source data.

2. Data Quality and Reconciliation

• Reconcile financial data against general ledger records, payroll files, and invoices every month.
• Verify financial figures before reports are shared with executives.
• Develop and maintain data validation rules and control checks.
• Investigate discrepancies and coordinate with the responsible teams to correct issues at their source.
• Maintain documentation and audit trails for internal reviews and client audits.

3. Financial and Operational Analysis

• Compare billable hours, full-time equivalent (FTE) counts, and customer interactions against invoiced amounts to identify revenue leakage and billing errors.
• Prepare account-level profit and loss (P&L) reports to explain changes in profitability.
• Analyze operational factors such as staffing, occupancy, attrition, overtime, training costs, and handle time to understand their financial impact.
• Evaluate profitability across different pricing models, including hourly, per-FTE, per-minute, per-transaction, and outcome-based arrangements.
• Analyze the cost of serving customers through human employees, AI solutions, and hybrid operating models.
• Explain financial concepts to Operations and Data Engineering teams and help Finance teams understand operational data.

4. Financial Reporting and Recommendations

• Prepare monthly and ad-hoc financial reports, including budget-versus-actual comparisons, period-over-period analysis, and client profitability reports.
• Investigate financial variances and identify their underlying operational or commercial causes.
• Present findings with measurable financial impact and practical recommendations.
• Present financial insights to senior management and client stakeholders.
• Adjust reports and presentations to suit the audience's level of technical and financial knowledge.

5. Technical Skills and Data Visualization

• Use SQL to retrieve, combine, and analyze data from different sources.
• Use Excel or Google Sheets for financial modeling, reporting, and reconciliation.
• Apply data modeling concepts, including facts, dimensions, data grain, master data, and metric definitions.
• Work with cloud data warehouses, preferably Snowflake, and dbt.
• Use Python for data analysis when needed.
• Use AI tools such as Claude to assist with queries, models, and documentation while reviewing outputs for accuracy.
• Create clear and accurate charts and dashboards that communicate trends, comparisons, distributions, and financial variances.
• Select appropriate visualizations and avoid misleading charts or presentation techniques.
• Prepare executive-level reports that highlight key findings and allow stakeholders to review supporting details.

Qualifications and Skills

Financial and Business Knowledge

• Strong understanding of profit and loss (P&L), cost of delivery, gross margin, unit economics, budgeting, and forecasting.
• Knowledge of revenue recognition, accruals, and month-end closing processes.
• Understanding of payroll and financial reporting across multiple countries and currencies, including foreign exchange (FX) treatment.
• Ability to connect operational performance, such as headcount, utilization, attrition, volume, and productivity, to financial results.

Technical Skills

• Strong SQL skills, including complex joins, window functions, and aggregations.
• Advanced Excel or Google Sheets skills for financial analysis and reconciliation.
• Knowledge of data modeling, master data management, and financial metric definitions.
• Familiarity with cloud data warehouses, preferably Snowflake, and dbt.
• Python experience is an advantage.
• Ability to use AI tools to support data analysis and review generated outputs critically.

Core Competencies

• Excellent attention to detail and commitment to financial data accuracy.
• Strong analytical and problem-solving skills.
• Ability to investigate issues and identify root causes.
• Clear written and verbal communication skills.
• Strong data storytelling and presentation skills.
• Ability to work effectively with Finance, Operations, and technical teams.
• Integrity and discretion when handling confidential payroll and financial information.
• Fluency in English and Spanish, with the ability to present findings to senior executives, is a PLUS.

Experience

• At least 5 years of experience in data analysis, with substantial experience working directly with financial data.
• Working knowledge of revenue recognition, accruals, and month-end closing processes.
• Experience reconciling financial records and maintaining controls over reported figures.
• Experience in accounting, financial planning and analysis (FP&A), or financial control is preferred.
• Experience in BPO, contact center, or other labor-driven service businesses is a strong advantage.
• 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.