Principal Data Engineer ​/ Financial Analyst

Red Hat will not be providing visa sponsorship for this position. Therefore, in order to be considered for this position, you must have the ability to work without a need for current or future visa sponsorship.*

Red Hat’s Global Sales Go-To-Market Strategy, Incentives & Data Analytics team is seeking a Principal Data Scientist / Financial Analysis professional to lead efforts to improve the accuracy, consistency, and strategic use of revenue, sales, and financial data across the organization.

In this role, you will apply advanced analytics, data science, and financial expertise to develop key revenue performance measures, support precise business planning, and deliver trusted insights across the end-to-end revenue lifecycle. You will analyze bookings, recurring revenue, renewals, expansion, contraction, customer retention, product performance, and other revenue drivers to help business leaders understand historical results, assess in-quarter performance, and improve future revenue outcomes.

This strategic position is responsible for designing scalable analytical and data-validation frameworks, automating data-quality and financial-reconciliation processes, and proactively identifying financial risks, revenue anomalies, and growth opportunities. You will help establish governance-grade reporting standards that provide stakeholders with accurate, timely, consistent, and auditable information.

The successful candidate will combine deep data science and analytical expertise with strong commercial and financial acumen. You will play a pivotal role in advancing automation, standardization, predictive analytics, financial analysis, and visibility across global sales, revenue, planning, and incentive processes.

You will serve as a trusted advisor to Sales, Finance, Operations, and executive stakeholders, translating complex financial and operational data into actionable insights that support revenue growth, forecasting, resource allocation, and strategic business decisions.

• Lead cross-functional initiatives to improve the accuracy, timeliness, completeness, and consistency of sales, revenue, and financial datasets used for planning, forecasting, performance measurement, and management reporting
• Develop advanced analytical models to evaluate revenue performance, including bookings, recurring revenue, renewals, retention, expansion, contraction, upsell, cross-sell, new business, and product- or customer-level revenue trends
• Analyze historical and in-quarter revenue performance to identify trends, performance gaps, financial risks, growth opportunities, and the underlying drivers of variance against plan, forecast, and prior-period results
• Build predictive and diagnostic models that improve revenue forecasting, customer-retention analysis, pipeline-conversion insights, and the identification of revenue at risk
• Partner with Finance and business-planning teams to reconcile operational revenue measures with financial results, ensuring alignment among sales activity, bookings, revenue recognition, forecasts, and management reporting
• Design and implement data-validation rules, pipeline-reconciliation dashboards, anomaly-detection models, and automated controls to ensure accounting-grade data integrity
• Establish automated checks to identify missing transactions, duplicate records, classification errors, unexpected revenue movements, product-mapping issues, timing differences, and inconsistencies across source systems
• Enforce data-submission calendars, lead recurring data-health reviews, and establish monthly and quarterly lock processes to maintain trusted, controlled, and auditable data workflows
• Standardize revenue definitions, classifications, financial measures, and business rules through collaborative reviews with Go-To-Market, Finance, Sales, Operations, and Incentives stakeholders
• Develop daily, weekly, monthly, and quarterly dashboards that surface revenue trends, performance anomalies, forecast risks, and key financial insights for business and executive stakeholders
• Perform variance analysis across actuals, targets, forecasts, and prior-period performance, clearly explaining the financial and operational drivers behind material changes
• Support annual and quarterly planning by developing analytical datasets and models for revenue targets, quota allocation, territory planning, capacity analysis, incentive design, and financial forecasting
• Curate and validate sales opportunity, bookings, customer, product, contract, and revenue data for use in incentives, quota modeling, territory design, performance reporting, and forecast-accuracy improvements
• Partner with Finance, Sales Operations, and reporting teams to develop trusted key performance indicators and scalable analytical tools supporting revenue planning, attainment, productivity, retention, and growth
• Apply statistical techniques and machine-learning approaches, where appropriate, to improve forecasting, segmentation, risk identification, pattern…