FinOps Data Analyst

Company Description

FinOpslyis an AI-native Value-Control platformfor cloud (AWS, AZ, GCP), data (Snowflake, Databricks), and AI economics, built to help enterprises move beyond passive cost visibility to active, outcome-driven control. The platform unifies technology spend across cloud infrastructure (AWS, Azure, GCP), data platforms (Snowflake, Databricks), and AI workloads into a single system of actioncombining planning, optimization, automation, and financial operations.

Role Description

We are seeking a highly motivated FinOps Data Analyst / Data Scientist to join our growing data organization. This role is ideal for early-career professionals who are passionate about data, analytics, and building scalable solutions that drive business impact.

You will work closely with engineering, FinOps SMEs, product managers, and business stakeholders to analyze cloud, financial, and operational data. The role combines analytical rigor, technical capability, and curiosity to translate complex datasets into actionable insights.

If you are analytically strong and want hands-on exposure to real-world AWS, Azure, GCP and Snowflake datasets, this role offers accelerated growth in cloud economics and cost optimization.

What you will do:

• Analyze AWS, Azure and GCP billing and Snowflake usage data
• Identify cost drivers, inefficiencies, and optimization opportunities
• Build SQL-based financial models and KPIs
• Support anomaly detection and forecasting for cloud spend
• Contribute to automation of cost optimization insights
  

What you bring:

• 3+ years of experience in financial data analysis, or data analytics in a cloud-native environment.
• Hands-on experience analyzing AWS CUR, Azure Billing Exports, or similar cloud consumption datasets preferred
• Strong proficiency in SQL, including complex joins, window functions, performance optimization, and building reusable analytical views.
• Experience working in Snowflake or comparable cloud data warehouse environments.
• Practical understanding of FinOps concepts: Preferred
• Ability to build and interpret financial KPIs and cost efficiency metrics.
• Proficiency in Python (Pandas, NumPy) for large dataset analysis and automation.
• Experience performing cost anomaly detection, trend analysis, and spend forecasting.
• Ability to translate technical cloud usage data into clear financial narratives for stakeholders (engineering, finance, leadership).
• Strong attention to detail, especially when working with reconciliation, billing validation, and financial accuracy.
• Solid foundation in statistics and data analysis
• Curiosity about cloud platforms and financial analytics
• Ability to work independently in a fast-paced startup

What You'll Gain:

• Exposure to enterprise-scale cloud billing datasets
• Hands-on experience with Snowflake and cloud cost engineering
• Real impact on financial decision-making for customers
• Accelerated path into FinOps Data Science or Cloud Optimization Engineering

If you are excited about applying data science to real financial outcomes in cloud and AI environments, we would like to connect.