Cloud FinOps Analyst

Disco•Austin, TX

About The Position

This role manages and optimizes cloud expenses within the Engineering organization, focusing on AWS infrastructure, Snowflake data platforms, and OpenAI/Anthropic API utilization. The analyst tracks consumption data, creates financial models, and collaborates with engineering teams to build cost-efficient systems.

Requirements

A minimum of 6–7 years of professional experience in cloud financial management, technology systems analysis, or engineering operations
Understanding of Snowflake credit structures and LLM pricing metrics (input/output tokens, context windows).
Knowledge of core AWS services, pricing models, and native cost management tools.
Proficiency in SQL and Python to extract and manipulate raw cloud billing data and API transaction logs.
Experience building technical dashboards in QuickSight or equivalent BI utilities.
Experience applying FinOps principles to consumption-based cloud and software services.
Competency in budgeting, forecasting, variance analysis, and ROI calculation.
Ability to translate complex cloud billing data into clear, actionable technical tasks for software and data engineers.
Analytical skills focused on solving optimization problems and reducing waste through automated solutions.
Authorization to Work in the U.S.: Candidates must be legally authorized to work in the United States without sponsorship now or in the future. DISCO is not currently sponsoring visas, including, but not limited to, H-1B, TN, or EAD, and we are not accepting visa transfers.

Responsibilities

Build and manage cost models tracking spend across OpenAI and Anthropic, breaking down costs by application, prompt/response tokens, and model types.
Audit Snowflake utilization to optimize virtual warehouse sizing, auto-suspend settings, and data storage lifecycles.
Track utilization trends to assist leadership in evaluating capacity purchases and pricing models for specialized vendors.
Monitor AWS consumption and propose optimization strategies, including infrastructure rightsizing and managing Savings Plans and Reserved Instances.
Build real-time alerting systems to identify spending spikes.
Develop and implement cloud governance guidelines and tagging policies to ensure accurate expense allocation across engineering teams.
Create and maintain financial reports, variance analyses, and dashboards using QuickSight to communicate expense trends to stakeholders.
Develop data-driven forecasts and annual budgets for cloud and AI expenses based on engineering product roadmaps.
Coordinate with engineering, data, and finance teams to negotiate vendor pricing and align technical operations with budget guidelines.