OPEN: FinOps Engineer

Job Overview

Looking for someone who has a passion for cloud financial management, cost optimization, and building automation at scale? We are seeking a FinOps Engineer to join our team and lead the implementation and operation of FinOps practices with a focus on Microsoft Azure. This role is ideal for someone with a strong cloud/infrastructure engineering background who also brings strong development and data engineering skills.
You will work with large datasets, APIs, and automation tools to support FinOps processes and contribute to the development of internal tooling that functions similarly to a SaaS application. In this role, you will collaborate with engineering, finance, and product teams to drive cost efficiency, transparency, and financial accountability in cloud operations.

Responsibilities will include:

• Cost Optimization: Analyze Azure cloud usage and spend to identify and implement cost-saving opportunities, including rightsizing, reservations, and eliminating waste.
• Data Engineering: Build and maintain ETL pipelines using Python to collect, transform, and aggregate Azure cost and usage data from multiple sources.
• Dashboarding & Reporting: Develop and maintain Grafana dashboards that provide actionable insights into cloud spend, usage trends, and optimization opportunities.
• Backlog Contribution: Work with the FinOps Product Owner to define, estimate, and deliver backlog items in Azure DevOps, contributing technical expertise to product planning.
• Automation: Automate routine FinOps tasks such as tagging enforcement, anomaly detection, and cost allocations.
• Collaboration: Partner with engineering, finance, and procurement teams to support budgeting, forecasting, and chargeback processes.
• Documentation: Create and maintain documentation for FinOps processes, tools, and best practices.
• Education: Advocate for FinOps best practices across the organization, helping teams understand the financial impact of their cloud usage.
• Governance & Compliance: Support governance and policy enforcement to ensure cloud resources are compliant with organizational standards.

Qualifications

Education:

• Bachelor’s degree in Computer Science, Software Engineering, Finance, or related field.
• FinOps Certified Practictioner or Microsoft Azure certifications are a plus
• Experience – 2+ years in cloud engineering, DevOps, data engineering, platform engineering or cloud financial management, with hands-on experience in Microsoft Azure.

Skills:

• Strong working knowledge of Azure services, billing, pricing, and cost management.
• Proficiency in Python for data processing, automation, ETL and API Integrations.
• Experience working with large datasets and formats such as JSON, CSV, and Parquet
• Strong understanding of REST APIs, data ingestion, and service-to-service integrations.
• Experience with Grafana for building dashboards and reports.
• Proficiency with KQL for analytics, dashboarding, and data exploration.
• Experience with PowerShell for scripting and automation tasks.
• Familiarity with Azure DevOps for backlog and workflow management.
• Solid understanding of cloud cost optimization strategies and tools.
• Analytical mindset with strong problem-solving skills and attention to detail.
• Excellent communication and collaboration abilities.
• Additional skills in Azure Data Factory, Databricks, SaaS/platform devleopment, or distributed data processing are a plus.
• Solid understanding of cloud cost optimization strategies and tools.
• Analytical mindset with strong problem-solving skills.
• Excellent communication and collaboration abilities.
• Additional skills in Azure Data Factory, Databricks, Parquet are a plus.

CPUS Engineering employs artificial intelligence (AI) tools as part of its recruitment process to enhance efficiency and consistency. These tools may assist with activities such as application screening, candidate evaluation, and summarization of interview feedback.

AI-generated outputs are intended to supplement, not replace, human judgment. All final hiring decisions are made by qualified human decision-makers who exercise professional discretion in reviewing and assessing candidate information alongside any AI-generated insights.

CPUS Engineering ensures that the use of AI in recruitment complies with all applicable employment laws, human rights legislation, and privacy regulations. The organization is committed to maintaining fairness, transparency, and non-discrimination throughout the hiring process.