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Intapp

Industry cloud solutions for professional services

FinOps & Product Analytics Engineer

Data Engineering +1Posted on Nov 12
Full-timeRemote

About the Job

Requirements

  • Strong SQL skills, including complex aggregations, window functions, joins across large datasets, and investigating data discrepancies before releasing results.
  • Python proficiency for writing clean, maintainable scripts for data transformation, normalization, and tooling.
  • Experience with analytical or columnar databases such as ClickHouse, BigQuery, Redshift, or DuckDB, or similar databases.
  • Demonstrated experience building with an LLM API such as Anthropic or OpenAI, including tool use, structured outputs, and reliable AI responses.
  • Ability to translate subject matter experts’ questions into accurate data models and queries based on well-defined requirements.
  • Comfort making sound architectural decisions in a greenfield environment where patterns are still being established.

Responsibilities

  • Design and maintain analytical data models, including schemas, views, and aggregations, to represent FinOps data such as cloud cost, cost allocation, anomaly signals, infrastructure usage, and unit economics, with additional domains to follow.
  • Build ingestion and normalization pipelines that clean and unify data from AWS and Azure billing, SaaS platforms, product telemetry, and internal systems into a consistent, queryable analytical layer.
  • Develop AI-powered reporting skills in Python using MCP (Model Context Protocol) to return structured answers to stakeholder questions about cost anomalies, team-level spending, usage trends, and future data domains.
  • Implement prompt engineering and output validation layers to improve AI answer reliability, including handling empty results, ambiguous time ranges, and conflicting data.
  • Build and maintain dashboards in Metabase for FinOps metrics such as showback, chargeback, anomaly signals, and unit costs, then expand them to additional domains.
  • Collaborate with FinOps experts, product managers, and domain leads to translate requirements into accurate data models and query patterns that reflect underlying data behavior.
  • Evaluate and contribute to architecture decisions as new data domains and source systems are added to the platform.
  • Document data models, AI skill patterns, and pipeline logic so the broader team can understand and extend the work.
  • Continuously improve data quality, query performance, and AI output reliability as the platform scales in volume, variety, and scope.

Desired Qualifications

  • Familiarity with MCP (Model Context Protocol) or similar function-calling and tool-use patterns for LLMs.

About the Company

Intapp

Industry cloud solutions for professional services

Intapp provides industry-specific cloud software and advisory services for professional and financial services firms. Its core product, OnePlace, links different operations to support the entire client lifecycle from strategy to execution, while helping modernize and secure IT systems. It differentiates itself by combining targeted software with hands-on transformation services and data activation to improve client outcomes and grow new business. The company aims to help firms achieve growth and better client experiences by aligning data, processes, and technology.

Company size
1,001-5,000
Company stage
IPO
Headquarters
Palo Alto, CA
Founded
2000

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