FinOps Data Engineer – AI Cost & Usage Analytics

About the role

Gorilla Logic is seeking a FinOps Data Engineer to build scalable data solutions that give visibility into AI usage, consumption, and costs across multiple platforms. You will work at the intersection of data engineering, cloud financial management, and AI operations.

Key responsibilities

• Design, build and maintain data pipelines that ingest AI usage and billing data from providers such as GitHub Copilot, Anthropic Claude, Google Gemini, OpenAI, Azure OpenAI, etc.
• Develop API integrations using Python, Cloud Functions, Cloud Composer/Airflow and ensure robust error handling, monitoring and data‑quality validation.
• Create a unified BigQuery data model that normalises usage and cost data and supports dimensional and analytical reporting.
• Build and optimise Power BI dashboards for AI spend visibility, cost allocation, forecasting and utilisation.
• Collaborate with FinOps, Finance, Engineering and other stakeholders to define metrics, KPIs and anomaly‑detection logic.

Required profile

• 3+ years of professional experience in data engineering, analytics engineering or software engineering.
• Strong proficiency in SQL and experience designing analytical data models.
• Hands‑on experience with Google BigQuery (or comparable cloud data warehouse).
• Experience building data pipelines with Python and workflow orchestration tools such as Apache Airflow or Google Cloud Composer.
• Proven ability to integrate with REST APIs, including authentication, pagination and rate‑limiting.
• Experience with Power BI dashboard development and data modelling.

Required skills

• Python
• SQL
• Google BigQuery
• Apache Airflow / Google Cloud Composer
• REST API integration
• Power BI
• Git version control
• CI/CD for data pipelines