FinOps AI Data Engineer, Principal

Design and scale a governed FinOps AI data platform that delivers enterprise visibility into cloud and generative AI consumption through reliable pipelines, models, and reporting.

Responsibilities

• Build and improve the FinOps data set, data model, and reporting pipeline, including integrations for AI usage and cost telemetry.
• Convert billing and allocation inputs into scalable reporting capabilities for: tokenomics, AI Gateway, AI DLC Tool, AI Agent Tool, LLM, workspace, user, AppID, use-case, order-number, model-provider, and model-name.
• Enable mandatory metadata ingestion, FinOps Data Lake integration, FOCUS-aligned AI data modeling, and the foundations for full-cost showback and AI chargeback reporting.
• Standardize and automate FinOps reporting and AI showback/chargeback views to support optimization insights, anomaly detection inputs, and related workflows.
• Expand data engineering capacity for Snowflake, PowerBI, Flexera, AI Gateway, external AI usage sources, and cloud provider cost data pipelines.
• Build and maintain AI usage telemetry, tokenomics datasets, allocation logic, unit economics inputs, and the reporting foundations for AI showback/chargeback.
• Automate data quality checks and refresh routines for: anomaly detection inputs, optimization insight pipelines, and consumption trend data for cloud and AI spend.
• Support inventory and data capture for LLM usage outside the Enterprise AI Gateway, including known external GenAI and SageMaker use cases.

Requirements

• BA/BS in computer science, management information systems, or related field of study, or equivalent work experience.
• 10+ years of experience across multiple data engineering and ETL ecosystems.
• 3+ years of experience in machine learning algorithm deployment and MLOps.
• Experience leading development teams.
• 5+ years building production-grade distributed data pipelines.
• Deep knowledge of multi-cloud billing mechanics, including AWS CUR and Azure FOCUS datasets, plus FinOps Framework principles.
• Proven experience tracking and modeling AI infrastructure costs, including LLM API usage, GPU clusters (examples: NVIDIA Triton, Kubernetes), and vector database spend.
• Hands-on experience with cloud data warehouses and lakehouses such as Snowflake, Databricks, BigQuery, or Amazon Redshift.
• Strong background designing schemas for complex financial allocation, amortization, shared-cost showback, and forecasting.
• Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related field; FinOps Foundation Certified (FOCUS) and a professional designation are desired.

Technologies

• Snowflake, PowerBI, Flexera, AI Gateway
• NVIDIA Triton, Kubernetes, vector database
• Databricks, BigQuery, Amazon Redshift
• AWS CUR, Azure FOCUS datasets
• FOCUS, LLM, SageMaker, GenAI
• FinOps Framework

Compensation

• USD 140,000 - 238,000 per year

Location and Work Type

• Oakland, CA (hybrid)
• Hybrid includes working from a remote office and in-person at the Oakland Corporate Office 1-2x per week or based on business needs/company requirements.
• HQ location is flexible within the Bay Area Region and will be agreed upon by the hiring leader and the successful candidate.

Job Details

• Job Category: Information Technology
• Job Level: Manager/Principal
• Business Unit: Technology & Security
• Work Type: Hybrid