Senior FinOps Analyst

Lifted, an Upwork Company™•Chicago, IL

9d•Remote

About The Position

We are seeking a Senior FinOps Analyst to advise engineering and R&D teams on cloud spending, investigate cost anomalies, and identify actionable optimization opportunities. In this role, you will serve as a primary partner-facing resource for APAC-based teams, helping align cloud spending with forecasts and measurable business outcomes through cost analysis, education, and proactive engagement. Enterprise experience is strongly preferred.

Requirements

Senior-level experience in FinOps (cloud financial operations).
Strong expertise in cloud cost management and optimization.
Proven ability to investigate spending anomalies and produce clear, written root-cause analyses.
Experience advising and consulting directly with R&D or engineering teams in a partner-facing capacity.
Experience with cloud cost forecasting, including aligning central forecasts with team-level projections.
Familiarity with OpenAI/LLM cost drivers and monitoring LLM spending.
Experience with cost modeling and tracking team investments or projects.
Proficiency with Jira for documenting investigations and Slack for real-time and asynchronous support.
Experience maintaining technical documentation or wiki spaces and contributing to recurring reporting, such as Showback.
Strong written and verbal communication skills, with the ability to engage stakeholders and communicate findings effectively.

Nice To Haves

AI/LLM governance expertise.
AI/LLM variable cost management expertise.

Responsibilities

Serve as a primary contact for engineering teams seeking cloud cost guidance, responding to questions in real time through Slack and other asynchronous channels.
Proactively engage with high-spending R&D teams to review monthly cloud spending, identify cost optimization opportunities, and understand upcoming engineering roadmap plans and their potential cost implications.
Capture meeting notes, recommendations, recurring questions, and emerging cost patterns.
Monitor cloud and AI/LLM spending for anomalies, spikes, and inefficiencies.
Investigate spending variances, produce written root-cause analyses, and recommend optimization opportunities to team owners.
Document investigations in Jira and flag relevant findings for monthly reporting.
Participate in monthly forecasting by reconciling central forecasts with team-level projections, documenting discrepancies, and capturing team plans and anticipated spending.
Contribute practitioner insights and team-sourced information, including AI/LLM cost drivers, to Showback reporting and spending reviews.
Support cloud cost awareness and education across engineering and R&D teams.
Audit and update technical wiki content and documentation.
Model team cost projections and track team investments and projects.
Respond to cost-related requests through Slack, email, and other communication channels.
Focus on advisory and analytical delivery. Central budget ownership, vendor contract modeling, and platform/tooling engineering are outside the scope of this engagement.