FinOps & Product Analytics Engineer

Intapp; United States; Hybrid; USD 90,000 - 130,000; Full time

Benefits offered by this job

Home-office stipend

Equity

Paid leave

Education reimbursement

Job summary

Intapp is building the data foundation and AI-assisted analytics to help engineering, product, and finance teams understand cloud costs and product usage. The work begins with FinOps data and expands to other domains, combining data modeling, pipeline development, reporting tools, and dashboards.

Role involves modeling cloud spend, building pipelines to normalize data from diverse sources, and developing Python-based AI reporting tools.

Qualifications

• Strong SQL skills with joins, aggregations, and window functions.
• Python for data transformation and tooling.
• Experience with analytical or columnar databases.
• Hands-on experience with LLM APIs and tool-use patterns.
• Ability to translate stakeholder requirements into data models and queries.

Responsibilities

• Model cloud spend, allocations, and unit economics.
• Build pipelines to normalize billing, SaaS, telemetry, and internal data.
• Develop Python-based AI reporting tools for spend, anomalies, and usage.
• Add prompt and output checks for missing data and unclear time periods.
• Create dashboards for cost allocation, anomalies, and unit costs.
• Collaborate with SMEs and product leaders to turn questions into data models and queries.

Skills

SQL

Python

Data modeling

ETL

Education

Bachelor's degree in CS/SE/Math

Tools

LLM API

Snowflake

BigQuery

Pandas

Job description

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.