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Cloud Infrastructure Cost Analyst (FinOps) - Remote

Posted 19 hours ago
Data Analysis
Full Time
Germany

Overview

We are looking for a Cloud Infrastructure Cost Analyst to help us understand, forecast, and optimize the cost structure of our cloud-based products.

In Short

  • Analyze cloud usage and infrastructure spend to understand the main cost drivers across our platform
  • Build and maintain reports on infrastructure cost (e.g. free vs paid tier usage, POC environments, product-level cost)
  • Work closely with the Cloud Engineering team to understand how architecture and resource usage affect cost
  • Develop models to estimate cost per customer, feature, or workload
  • Forecast infrastructure spend based on usage trends and upcoming changes in our architecture
  • Identify opportunities for cost optimization (e.g. savings plans, resource sizing, usage patterns)
  • Build internal dashboards and simple tools to make cloud cost data accessible to engineering, finance, and sales
  • Support internal teams with data for pricing, deal modeling, and infrastructure planning

Requirements

  • Strong analytical skills and experience working with Python and SQL
  • Experience analyzing large datasets and building reports or dashboards
  • Familiarity with public cloud platforms (AWS, GCP, or Azure) and a basic understanding of infrastructure components such as compute, load balancing, and serverless workloads
  • Ability to translate technical usage data into cost models, forecasts, or business insights
  • Comfortable working with engineers and understanding how cloud architecture and resource usage affect cost
  • Experience working with modern data platforms (e.g. Snowflake or similar)

Benefits

  • Shape the future of AI infrastructure
  • Work with a globally distributed, high-talent team
  • Competitive compensation + equity
  • Remote-first culture
Qdrant logo

Qdrant

Qdrant is an innovative technology company that specializes in open-source vector databases tailored for next-generation AI applications. Their platform facilitates high-performance vector similarity search, enabling users to extract deep insights from unstructured data. By providing both open-source software and managed cloud solutions, Qdrant empowers developers and enterprises to effortlessly create scalable, AI-driven search and recommendation systems.

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