FinOps Engineer, Cost Analytics & Platform

BlackLine•Pleasanton, CA

20d•$116,000 - $145,000•Hybrid

About The Position

The FinOps Engineer, Cost Analytics & Platform drives cloud cost analysis, forecasting, optimization, and executive reporting across GCP, AWS, and Azure. The role is the primary owner of Apptio Cloudability and the FinOps reporting layer. Although titled and leveled as an engineering role, its day-to-day work is analytical: turning cost data into decisions, building executive-facing dashboards, and partnering with Finance and Engineering to optimize spend. The role queries the cost data lake directly, builds lightweight automation for recurring reporting, and partners closely with the FinOps Engineer, Data Platform on data and pipeline requirements. AI/LLM spend, including platforms such as Anthropic and OpenAI, is a first-class part of forecasting and reporting alongside traditional multi-cloud spend. BlackLine describes its culture as open, accepting, and supportive of employee growth and learning, with professional development seminars and inclusive affinity groups. The company uses a combination of virtual and in-person work. Candidates living within a reasonable commute of an office are expected to work in the office at least three days a week.

Requirements

At least 4 years of experience in FinOps, cloud cost management, cloud financial analysis, or a closely related area such as financial analysis with strong cloud exposure.
Hands-on expertise with a cloud cost management platform; able to independently build reports, configure allocations, and manage tagging and folder structures. Apptio Cloudability is strongly preferred.
Strong working knowledge of cloud pricing and optimization across at least two of GCP, AWS, and Azure, including committed use discounts, savings plans, reserved instances, and rate structures.
SQL proficiency sufficient to self-serve directly from the BigQuery data lake rather than relying solely on delivered dashboards.
Demonstrated ability to build clear, accurate, executive-ready dashboards and analysis with minimal rework.
Strong financial modeling and Excel skills, including forecasting, variance, and scenario analysis.
Excellent written and verbal communication skills, including presenting cost analyses to senior leadership and tailoring information to the audience.

Nice To Haves

FinOps Foundation certification, such as FinOps Certified Practitioner or higher.
Experience tracking and forecasting AI/LLM platform spend, with a working understanding of usage-based AI pricing, token or consumption metrics, and cost drivers.
Python or comparable scripting experience for reporting automation.
Experience with multi-cloud environments and large-scale commitment portfolios.
Familiarity with SaaS/cloud-hosting unit economics and chargeback maturity models.

Responsibilities

Own Apptio Cloudability as the primary FinOps platform, including cost allocation and tagging structures, folder and report configuration, business mappings, and chargeback/showback readiness.
Build and maintain executive-facing Looker Studio and Cloudability dashboards for cloud cost, unit economics, commitment savings, and variance.
Produce recurring FinOps reporting, including the weekly P&T showback email, DCU dashboard narratives, and ExCo/QBR contributions, to a quality standard requiring minimal review.
Lead cost optimization analysis covering committed use discounts, savings plans, reserved instances, idle resource cleanup, and rate and commitment modeling across GCP, AWS, and Azure.
Build and maintain forecast and scenario models, including AI/LLM platform spend, contract-versus-list-rate impacts, migration costs, commitment renewals, and AI usage growth.
Query the BigQuery cost data lake directly using SQL for ad hoc analysis; define data and reporting requirements for the Data Platform engineer and validate delivered datasets.
Build lightweight SQL or scripting automation to reduce manual effort in recurring reporting.
Partner with Finance on GL treatment, accruals, and variance explanations, translating cloud and AI spend into financial terms for non-technical stakeholders.
Lead vendor and stakeholder conversations with Apptio/IBM, cloud account teams, and AI platform vendors on tooling, telemetry, and roadmap matters affecting cost visibility.