FinOps & Product Analytics Engineer

Role overview Build the data foundation and AI-assisted analytics that help engineering, product, and finance teams understand cloud costs and product usage. The work begins with FinOps data and is expected to expand to other domains, combining data modeling, pipeline development, reporting tools, and dashboards.

Responsibilities - Model cloud spend, allocations, infrastructure usage, anomaly signals, and unit economics in a consistent analytical layer. - Build pipelines to normalize billing, SaaS, telemetry, and internal data from varied sources. - Develop Python-based AI reporting tools that answer questions about spend, anomalies, and usage with structured, dependable results. - Add prompt and output checks to handle missing data, unclear time periods, and conflicting information. - Create and maintain dashboards for cost allocation, anomalies, and unit costs. - Work with subject matter experts and product leaders to turn questions into accurate data models and queries; document and improve the resulting systems.

Requirements - Strong SQL skills, including complex joins, aggregations, and window functions, with care to investigate unexpected results. - Python skills for maintainable data transformation and tooling. - Experience with an analytical or columnar database. - Hands-on experience building with an LLM API, including tool use or structured outputs. - Ability to translate stakeholder requirements into reliable data models and queries, and make sound choices in an evolving technical environment.

Nice to have - Familiarity with MCP or comparable function-calling and tool-use patterns for LLMs.

Benefits and work setup The listing describes a flexible work environment, performance-based compensation, equity, a home-office stipend, paid leave, continuing-education reimbursement, and potential travel to other development centers.