Staff Engineer, FinOps

GEICO

Confirmed live yesterday High trust
Remote

Quick summary

Work type
Remote
Location
Bethesda, MDPalo Alto, CANew York, NYRichardson, TX
Salary
$110,000–$230,000 / yr
Posted
45 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $212k
This role $170k
$93k most similar roles pay here $270k

This role pays less than 84% of similar roles. Most pay $185,300–$238,250 — the shaded band above. At the midpoint, this role pays about $170k versus about $212k for comparable roles.

Based on 240 similar postings.

Employer

About GEICO

GEICO (Government Employees Insurance Company) is one of the largest auto insurers in the United States, offering affordable auto, home, renters, and other personal insurance products. Industry: Insurance

GEICO currently has 68 open roles on FindRole.

Listed pay typically runs $112,500–$230,000 across 68 roles with salary data.

Most-posted roles

View all roles at GEICO

At a glance

TL;DR · Staff Engineer, FinOps

Staff Engineer – FinOps joins the Capacity and Workload Management organization within the FinOps and Cloud Optimization team. This role focuses on leading FinOps Engineering projects, including cost optimization, budgeting, forecasting, and capacity planning across cloud services. The engineer will develop automation strategies for business processes, establish spend reporting, define KPIs for executives, and manage stakeholder communications regarding cloud operational expenses. Technical responsibilities include providing thought leadership in full-stack web development, mentoring other engineers, and ensuring seamless integration between microservices and backend systems. The role requires expertise in AWS, Azure, or GCP environments, along with proficiency in Python, Django, gRPC, Kafka, Apache Spark, Java, TypeScript, ReactJS, BootstrapJS, Golang, Docker, Kubernetes, and Terraform. This position addresses the critical business problem of managing cloud costs while optimizing performance across complex infrastructure layers.

What does a Engineer earn in California?

Median $208000 from 94 postings across 22 companies.

See salary data

What you'll do

  • Lead FinOps engineering projects focused on cloud service cost optimization and capacity planning.
  • Develop and implement automation strategies to streamline business processes and improve spend reporting.
  • Create comprehensive strategies to enhance savings, governance, and overall operational efficiency.
  • Manage budget requirements, forecasting, and reporting in collaboration with business leaders and partner teams.
  • Define FinOps KPIs for IT executives and manage communications with senior leadership and financial controllers.
  • Develop Economic Units using business metrics to manage cloud operational expenses effectively.
  • Provide technical leadership and mentorship to engineers regarding system architecture and implementation.
  • Deploy web applications in Kubernetes environments ensuring seamless integration between backend services and cloud systems.

What we're looking for

  • Bachelor's degree in computer science, Information Systems, or equivalent education or work experience.
  • 8+ years of experience working in FinOps projects and understanding of FinOps concepts preferred.
  • 5+ years of experience in budgeting, forecasting, cost savings, and reporting using various tools.
  • 4+ years of experience in open-source frameworks and cloud technologies like Azure, AWS, or GCP.
  • 3+ years of experience with cloud architecture and design including cost optimization, capacity planning, pricing, and performance tuning.
  • 2+ years of professional software development or solutions engineering experience with technologies such as Java, TypeScript, ReactJS, Python, Golang, Docker, Kubernetes, or Terraform.
  • Experience designing and developing microservices using Python, Django, gRPC, Kafka, and Apache Spark.
  • Deep understanding of cloud services, pricing models, billing structures, and infrastructure for cost analysis and optimization.

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