Principal Cloud Finops Analyst

Horizon3 AI

1d•$240,570 - $297,000•Remote

About The Position

Horizon3.ai is seeking an experienced Cloud FinOps practitioner to provide visibility into cloud costs and margins, enabling leadership to make data-driven decisions for optimizing cloud spend. This role is crucial for understanding the costs associated with providing product features to customers and ensuring efficient resource utilization within our cloud environment.

Requirements

Significant experience as a FinOps cloud spend analyst on a major cloud provider.
Deep familiarity with cost and usage data and SQL based billing analysis, preferably on AWS.
Strong exploratory data analysis skills in SQL.
Ability to analyze and explore large, complex billing datasets.
Experienced in analysis of a cloud vendor’s billing data in SQL.
Able to independently investigate anomalies, identify cost drivers, and answer questions on spend.
Experience in a FinOps role at a B2B SaaS company with a multi-tenant architecture.
Familiarity with the challenge of attributing shared infrastructure costs to specific customers or product features.
Must have built cost reporting and dashboards for spend visibility.
Spreadsheet skills.
Ability to build forecasting models in Excel/Google Sheets.
Experience working with Engineering on tagging and labelling and driving cost visibility into development processes.
Familiarity with AWS/GCP/Azure savings mechanisms — Savings Plans, Committed Use Discounts, Reserved Instances, Spot Instances, etc.
Strong communication skills.

Nice To Haves

FinOps Foundation certification (FOCP or practitioner level) or equivalent demonstrated knowledge of FinOps frameworks and lifecycle.
Experience in BI tooling such as AWS QuickSight, GCP Data Studio, Tableau, Looker, or similar.

Responsibilities

Build spend visibility dashboards broken down by product, product feature, tenant, and team.
Partner with Engineering infra and product teams to define tagging taxonomy, identify tagging gaps, and improve tagging to enable reporting.
Make Cloud and AI spend billing data available in analytics and reporting tools, and with automated export to Excel / Google Sheets and finance systems.
Develop cloud spend forecast models that incorporate sales forecasts and product roadmap initiatives.
Define spend alarms based on budgets and forecasts.
Drive investigations of spend incidents.
Build capabilities to track unit economics of the product portfolio.
Partner with product feature teams to drive visibility on metrics such as cost per customer, per operation, per API request, and AI token usage rates.
Work with Infra teams on classification of infrastructure and utilization metrics.
Independently spend anomaly investigations, document findings, and make well defined clear recommendations.
Present spend findings to both Engineering and Finance leaders.
Translate and map between infrastructure details and business value.