Staff Business Analytics Engineer

Ridgeline

Staff Analytics Engineer leading FinOps, forecasting, cost allocation, and engineering performance analytics. Ridgeline’s investment-management software platform uses insights to optimize technology investments and operations.

Posted 8/17/2026full-timeNew York City • California, New York • 🇺🇸 United StatesLead💰 $200,500 - $251,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in FinOps analytics, financial forecasting, and cost allocation methodologies, with a strong ability to communicate insights to diverse stakeholders. Proficient in building scalable data models and dashboards while driving high-impact analytical initiatives.

Highest-signal resume keywords

FinOps AnalyticsFinancial ForecastingSQL SkillsCost Allocation MethodologiesDashboard Development

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Business AnalyticsAnalytics EngineeringFinancial AnalyticsUnit Economic ModelsScenario AnalysesCost Drivers AnalysisData Quality PracticesAnalytical FrameworksPerformance MetricsCloud Cost Analysis

Soft Skills

Problem-Solving SkillsCommunication SkillsInfluencing Without AuthorityBuilding Trusted PartnershipsContinuous Improvement Mindset

Tools & Technologies

AWSAzureGCPSnowflakeDatabricksBI PlatformsAI ToolsSelf-Service AnalyticsData Visualization ToolsReporting Systems

Industry Keywords

Cloud Cost AllocationChargeback/ShowbackCapacity PlanningEngineering OperationsR&D OperationsOperational WorkflowsFinancial ReportingOperational ReportingTechnology SpendUtilization Optimization

Tech Stack

Tools & technologies

AWSAzureCloudGoogle Cloud PlatformSQL

About the role

Key responsibilities & impact

Own and evolve FinOps analytics covering technology spend, cost drivers, utilization, efficiency, and optimization opportunities
Develop unit economic models connecting infrastructure and technology costs to product, customer, workload, and business drivers
Build forecasts for cloud, infrastructure, tooling, and engineering costs
Analyze actual performance against forecasts, identify variance drivers, and recommend actions to Engineering and Finance leaders
Establish allocation and attribution methodologies for products, services, environments, and workloads
Partner with Engineering, Finance, and business leaders to evaluate cost, performance, reliability, growth, and customer-impact tradeoffs
Define metrics and analytical frameworks for engineering organizational performance
Build scalable data models, dashboards, and self-service analytics
Identify trends, anomalies, and optimization opportunities and drive investigations through recommendations
Develop scenario and sensitivity analyses for architecture, usage, growth, pricing, and engineering investments
Establish data quality and validation practices for financial, operational, and engineering reporting
Communicate complex financial and operational insights to technical and non-technical audiences
Drive ambiguous, high-impact analytical initiatives from problem definition through implementation, adoption, and measurable outcomes
Contribute to learning, teaching, experimentation, and continuous improvement

Requirements

What you’ll need

Significant experience in business analytics, analytics engineering, FinOps, financial analytics, business intelligence, or a related discipline
Demonstrated ability to lead complex, ambiguous analytics initiatives and influence strategic decisions at Staff level
Experience analyzing cloud, infrastructure, technology, or complex cost structures and identifying spend drivers
Experience developing financial forecasts, unit economic models, cost allocation methodologies, scenario analyses, or similar decision-support models
Strong SQL skills and experience transforming complex datasets into reliable, reusable analytical models
Strong financial and analytical acumen connecting technical and operational metrics to financial and business outcomes
Experience developing dashboards, reporting systems, and self-service analytics
Ability to translate ambiguous business questions into metrics, analytical approaches, and recommendations
Strong problem-solving skills and ability to identify patterns, investigate root causes, and navigate incomplete information
Ability to communicate complex analytical and financial concepts to technical and non-technical stakeholders
Ability to build trusted partnerships and influence without authority across Engineering, Finance, and other functions
Willingness to explore cutting-edge technologies and AI tools while developing expertise in engineering operations and FinOps
Serious interest in having fun at work
Must be work authorized in the United States without employer sponsorship
Bonus: experience with cloud-native or SaaS FinOps; AWS, Azure, GCP, Snowflake, or Databricks cost analysis; cloud cost allocation, tagging, chargeback/showback, commitments, capacity planning, and optimization; engineering or R&D operations; engineering productivity and organizational health metrics; modern data transformation, visualization, and BI platforms; AI-assisted analytics, forecasting, reporting, or operational workflows

Benefits

Comp & perks

Company Stock Plan, subject to the applicable Stock Option Agreement
Unlimited vacation
Educational reimbursements
Wellness reimbursements
$0 cost employee insurance plans
Career advancement opportunities