FinOps AI Data Engineer, Principal

PG&E Corporation is hiring a FinOps AI Data Principal to shape and scale the core FinOps Data Platform. In this hybrid role based in Oakland, you will build governed data pipelines, models, and reporting that provide enterprise visibility into cloud and generative AI consumption, with AI showback/chargeback readiness and optimization-focused analytics.

What you’ll do

• Design, build, and continuously improve the FinOps dataset, data model, reporting pipeline, and AI usage and cost telemetry integrations.
• Convert requirements from billing and allocation through AI telemetry sources into scalable data structures and reporting capabilities, including tokenomics, AI Gateway, AI DLC Tool, AI Agent Tool, LLMs, workspace and user details, AppID, use-cases, order numbers, model providers, and model names.
• Establish foundations for mandatory metadata ingestion, FinOps Data Lake integration, FOCUS-aligned AI data modeling, full-cost showback dependencies, and AI chargeback reporting.
• Standardize, simplify, and automate FinOps reporting, AI showback/chargeback views, optimization insights, anomaly detection inputs, and related process workflows.
• Increase data engineering capacity across Snowflake, Power BI, Flexera, AI Gateway, external AI usage sources, and cloud provider cost data pipelines.
• Build and maintain AI usage telemetry and tokenomics datasets, including allocation logic and unit economics inputs to support AI showback and chargeback reporting.
• Automate data quality checks, reporting refreshes, anomaly detection inputs, optimization insight pipelines, and consumption trend data for both 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.

Qualifications

• BA/BS in computer science, management information systems, or a 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 machine learning operations.
• 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, along with FinOps Framework principles.
• Proven experience tracking and modeling AI infrastructure costs, including LLM API usage, GPU clusters (such as NVIDIA Triton and 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 a related field; FinOps Foundation Certified (FOCUS) and a professional designation desired.

Tools and technologies

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

Location: Oakland, CA (hybrid). Work type: Hybrid working from a remote office and in-person at the Oakland Corporate Office 1-2x per week or based on business needs or company requirements.

Compensation: USD 140,000 - 238,000 per year. Job category: Information Technology. Job level: Manager/Principal. Business unit: Technology & Security.

HQ location: Flexible within the Bay Area Region and will be agreed upon by the hiring leader and successful candidate.