## About the Role

Freudenberg is hiring a FinOps Analyst to support cloud and AI cost management across the business. The role focuses on turning usage, cost, contract, and operational data into reliable reporting and actionable insights for forecasting, allocation, and decision-making.

You will work closely with stakeholders across IT, Finance, Controlling, Procurement, and Management. The position is designed to improve visibility into cloud and AI spending, support cost governance, and help identify opportunities to optimize resources, budgets, and consumption models.

A key part of the role is establishing and maintaining the data, standards, and reporting needed to support FinOps practices across cloud services and AI workloads. This includes helping teams evaluate spend, track commitments, and make informed choices about scaling, continuing, or adjusting initiatives.

## Key Responsibilities

– Consolidate and validate cloud and AI cost, usage, contract, license, and operational data for reporting, forecasting, allocation, and decision-making.
– Define and maintain measurement dimensions, tagging and metadata standards, and allocation models across business units, products, applications, projects, environments, and owners.
– Analyze cost drivers and unit economics across cloud services and AI workloads, including compute, storage, data transfer, licenses, tokens, model usage, GPU/CPU consumption, and transactions.
– Compare actual spend with budgets, forecasts, business cases, TCO, commitments, and targets to identify trends, risks, and optimization opportunities.
– Lead or support regular cost, usage, and forecast reviews with technical and business stakeholders.
– Monitor budgets, thresholds, quotas, and commitments, and escalate deviations when needed.
– Identify anomalies, underused or overprovisioned resources, inefficient service or model choices, and unused contractual benefits.
– Coordinate optimization initiatives and track expected and realized savings.
– Provide cost, usage, and value insights to support decisions on scaling, continuing, or stopping AI initiatives.
– Develop policies, standards, and guardrails for tagging, budgets, approved services and AI models, regions, quotas, commitments, and approval processes.
– Build dashboards, recurring reports, and decision materials for IT, Finance, Controlling, Procurement, and Management.
– Automate recurring data collection, reporting, alerts, allocation, and optimization tracking.
– Coordinate key FinOps activities, including forecasting, budgeting, month-end processes, anomaly reviews, and optimization planning.

## Required Skills

– University degree in Business Informatics, Computer Science, Business Administration, Finance/Controlling, or a comparable field; relevant vocational training with practical experience is also acceptable.
– 1–4 years of relevant experience in FinOps, cloud cost management, IT controlling, data analytics, cloud operations, or a similar environment.
– Good understanding of cloud and AI consumption-based cost models.
– Practical exposure to cost allocation, tagging, budgeting, forecasting, showback/chargeback, unit economics, TCO, reporting, or anomaly analysis.
– Initial hands-on experience with cloud cost management, BI/reporting, or data analytics tools.
– Strong analytical and structured mindset.
– Numerical confidence and close attention to detail.
– Ability to translate cost and usage data into clear insights, recommendations, and follow-up actions.
– Collaborative, proactive, and reliable working style with ownership and a pragmatic, solution-oriented approach.
– Ability to communicate effectively with technical and commercial stakeholders in an international environment.
– Very good English skills.
– Additional German language skills are an advantage.

## Preferred Skills

– Experience with Power BI, SQL, APIs, or scripting.
– Knowledge of AI-specific cost drivers and consumption metrics such as tokens, model calls, GPU usage, agents, and transactions.
– Interest in developing further FinOps expertise.
– Familiarity with FinOps principles or certification.

## Cloud Platforms & Technologies

### Cloud Platforms
– Cloud services
– AI workloads
– Cloud and AI consumption-based cost models

### FinOps Platforms / Practices
– FinOps
– Cost allocation
– Tagging
– Showback
– Chargeback
– Budgeting
– Forecasting
– TCO
– Anomaly analysis
– Month-end processes
– Optimization tracking

### Data & Analytics
– Power BI
– SQL
– APIs
– Scripting
– Dashboards
– Reporting
– Data analytics tools

### AI-Related Metrics
– Tokens
– Model calls
– GPU usage
– CPU consumption
– Agents
– Transactions
– Model usage

## FinOps Responsibilities

– Consolidate cloud and AI cost and usage data for reporting, forecasting, and allocation.
– Maintain tagging, metadata, and allocation standards.
– Analyze cloud and AI unit economics and consumption drivers.
– Review actual spend against budgets, forecasts, business cases, TCO, and commitments.
– Monitor budgets, thresholds, quotas, and commitments.
– Identify anomalies, inefficiencies, and underutilized resources.
– Coordinate optimization initiatives and savings tracking.
– Support decisions on scaling or stopping AI initiatives.
– Establish policies and guardrails for cost governance.
– Automate reporting, alerts, allocation, and optimization tracking.
– Coordinate forecasting, budgeting, month-end processes, anomaly reviews, and optimization planning.

## Benefits

– Flexible work models.
– Meal allowance.
– Corporate events.
– Easy access by car or public transport.
– Inclusive working environment with a focus on diversity and inclusion.

## Why You Might Be Interested

This role offers the opportunity to work at the intersection of cloud, AI, finance, and operations in a role with clear business impact. It is well suited to someone who wants to build and apply FinOps expertise across both cloud services and AI workloads. The position also provides exposure to a wide range of stakeholders, including IT, Finance, Controlling, Procurement, and Management. With responsibilities spanning reporting, governance, optimization, and automation, the role offers breadth as well as strong analytical ownership.