Staff Business Analytics Engineer

Jobtailor

California (MO)

On-site

USD 140,000 - 210,000

Full time

6 days ago

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Job summary

Jobtailor is seeking a Senior FinOps Analytics leader to own and evolve cost analytics across technology spends, utilization, and optimization opportunities. You will build unit economics models linking infrastructure costs to business drivers and develop forecasts for cloud and engineering expenses.

You will partner with Engineering and Finance to evaluate tradeoffs, establish allocation methodologies, and deliver scalable data models and self-service analytics.

Qualifications

Significant experience in business analytics, analytics engineering, FinOps, financial analytics, BI, or related discipline.
Experience leading complex analytics initiatives and influencing strategic decisions at Staff level.
Experience analyzing cloud, infrastructure, or cost structures and identifying spend drivers.
Experience developing forecasts, unit economic models, cost allocation methodologies, and scenario analyses.

Responsibilities

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

Skills

SQL skills

Financial forecasting

Cost allocation

Unit economics

Dashboard development

Data modeling

Data quality

Cloud cost analysis

Tools

AWS

Azure

GCP

Snowflake

Databricks

BI platforms

Self-Service Analytics

Data Visualization

Reporting Systems

Job description

• 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

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

Core Competencies

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.

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