# FinOps Program Manager

**Company:** [Plaid](https://hotfix.jobs/companies/plaid)
**Location:** San Francisco, CA
**Role:** Technical Program Management
**Salary:** $173k – $259k/yr
**Experience:** 6+ years
**Skills:** SQL, Aws Cost Explorer, Gcp Billing, Azure Cost Management, Cloudhealth, Cloudability, Mode, Tableau, Looker, Finops, Kubernetes, Data Pipelines, BI Tools
**Posted:** 2026-05-08

> Leads FinOps initiatives to monitor, forecast, and optimize engineering spend on cloud, AI/ML, data, and SaaS across Plaid. Partners with engineering, product, and finance teams to drive cost-aware decisions and implement visibility tools. Requires 6+ years experience at engineering-finance intersection with SQL and cloud cost expertise.

## Job Description

## Responsibilities
- Monitors and analyzes engineering spend across cloud, AI/ML, data platforms, and SaaS, identifying trends, anomalies, and optimization opportunities.
- Builds and maintains forecasts for engineering spend, partnering with Finance and engineering leaders to understand drivers, assumptions, and risks.
- Partners with engineering, product, and TPMs to incorporate cost considerations into roadmaps, architectural decisions, and execution plans.
- Leads cost optimization initiatives, such as rightsizing, commitment strategies, and workload efficiency improvements, in collaboration with engineering owners.
- Creates and maintains dashboards and reporting that make spend understandable and actionable for both engineers and executives.
- Implements FinOps practices and processes, including showback/chargeback models, unit economics, and cost ownership frameworks.
- Partners on tooling and automation, working with data and engineering teams to improve cost visibility, forecasting accuracy, and operational efficiency.
- Drives alignment and behavior change, helping teams balance cost, performance, reliability, and velocity through data-driven decision making.

## Requirements
- 6–10+ years of relevant experience working at the intersection of engineering, infrastructure, data, or finance in a cloud-native or SaaS environment.
- Proven experience partnering closely with engineering teams to influence decisions involving cloud infrastructure, data platforms, AI/ML workloads, or SaaS spend.
- Working understanding of modern cloud-native architectures, including core components such as compute, storage, networking, data pipelines, and managed services—enough to engage credibly with engineers on design, tradeoffs, and cost drivers.
- Strong foundation in cost analysis, forecasting, budgeting, and variance management, with the ability to translate data into clear, actionable insights.
- Comfort working directly with data, including writing **SQL** (or effectively using AI-assisted tools to do so) to explore datasets, validate assumptions, and answer ad hoc questions.
- Experience building clear, high-quality dashboards and BI artifacts that are not only accurate, but intuitive and delightful for engineers and leaders to use.
- Demonstrated success driving adoption and behavior change—embedding cost awareness into day-to-day engineering workflows, not just producing reports.
- Experience owning and delivering cross-functional programs end-to-end, often without direct authority or a dedicated team.
- Familiarity with FinOps principles and practices (e.g., shared ownership, showback/chargeback, unit economics, optimization strategies).
- Strong communication skills, with the ability to tailor complex technical and financial concepts for engineering, finance, and executive audiences.

## Nice to Haves
- Hands-on familiarity with cloud cost management tools (e.g., **AWS Cost Explorer**, **GCP Billing**, **Azure Cost Management**, **CloudHealth**, **Cloudability**).
- Experience working with or supporting data platforms and AI/ML workloads, including understanding cost drivers for batch processing, streaming, storage, and model training/inference.
- Exposure to showback/chargeback models, cost allocation strategies, or product-level unit economics.
- Experience improving data models or pipelines that support analytics, reporting, or financial attribution.
- Familiarity with BI tools such as **Mode**, **Tableau**, **Looker**—and a strong eye for dashboard usability and design.
- Background in a technical role (e.g., engineering, TPM, infra, data, or engineering operations) before moving into a more cross-functional or business-oriented position.
- Experience operating in a high-growth or rapidly scaling environment, where cost structures and investment priorities are evolving quickly.

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