This role pays more than
75%
of similar roles. Most pay
$153,375–$205,200
— the shaded band above.
At the midpoint, this role pays about
$205k
versus about
$179k
for comparable roles.
Based on 240 similar postings.
Employer
About Plaid
Plaid is a financial technology company that builds a data network powering digital finance applications, enabling consumers to securely connect their financial accounts to apps and services. Industry: Financial Technology & Data Infrastructure
Plaid currently has
35 open roles
on FindRole.
Listed pay typically runs
$190,800–$262,800
across 35 roles with salary data.
The FinOps Program Manager joins a team operating at the intersection of Engineering, Product, and Finance to ensure spending is transparent and aligned with product strategy. This role focuses on financial accountability for engineering-related spend, including cloud infrastructure, AI/ML workloads, data platforms, and third-party SaaS tools. The manager will monitor spend trends, build accurate forecasts, lead cost optimization initiatives like rightsizing and commitment strategies, and create intuitive dashboards to make costs actionable. Key responsibilities include implementing showback models, unit economics, and cost ownership frameworks while driving behavior change across engineering teams. Required skills include experience with cloud-native architectures, SQL for data exploration, and proficiency in cost analysis and variance management. The role addresses the challenge of balancing cost, performance, and reliability within a complex technical environment involving large-scale data pipelines and model inference.
Monitor and analyze engineering spend across cloud infrastructure, AI/ML workloads, data platforms, and SaaS tools.
Build and maintain accurate financial forecasts for engineering spend by identifying key drivers and risks.
Lead cost optimization initiatives such as rightsizing, commitment strategies, and workload efficiency improvements.
Create and maintain intuitive dashboards to make spending data actionable for engineers and executives.
Implement FinOps practices including showback/chargeback models, unit economics, and cost ownership frameworks.
Develop tools and automation to improve cost visibility and forecasting accuracy.
Drive behavior change by embedding cost awareness into daily engineering workflows and decision-making processes.
What we're looking for
6–10+ years of relevant experience in engineering, infrastructure, data, or finance within a cloud-native or SaaS environment.
Proven experience partnering with engineering teams to influence decisions regarding cloud infrastructure, data platforms, AI/ML workloads, and SaaS spend.
Experience managing AI and machine learning spend, including tracking usage costs, forecasting budgets, and identifying optimization opportunities.
Working understanding of modern cloud-native architectures, including compute, storage, networking, and managed services.
Strong foundation in cost analysis, forecasting, budgeting, and variance management to provide actionable insights.
Ability to work directly with data by writing SQL or using AI-assisted tools to explore datasets and validate assumptions.
Experience building high-quality dashboards and BI artifacts that are intuitive for both engineers and executives.
Familiarity with FinOps principles such as showback/chargeback models, unit economics, and cost ownership frameworks.