What You Will Do
Design and maintain analytical data models — schemas, views, and aggregations — that correctly represent FinOps data including 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 heterogeneous sources — 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) that return structured, reliable answers to stakeholder questions — covering cost anomalies, team-level spend breakdowns, usage trends, and more as new domains come online.
Implement prompt engineering and output validation layers that make AI-generated answers trustworthy — handling empty results, ambiguous time ranges, and conflicting data gracefully.
Build and maintain dashboards in Metabase covering FinOps metrics (showback, chargeback, anomaly signals, unit costs) and expanding to additional domains as the platform grows.
Collaborate with FinOps experts, product managers, and other domain leads to translate requirements into accurate data models and query patterns that reflect how the underlying data actually behaves.
Help evaluate and contribute to architecture decisions as new data domains and source systems are brought into the platform.
Document data models, AI skill patterns, and pipeline logic so the broader team can understand, extend, and trust what you build.
Continuously improve data quality, query performance, and AI output reliability as the platform scales in volume, variety, and scope.
What You Will Need
Strong SQL skills — complex aggregations, window functions, joins across large datasets, and the instinct to investigate when a number looks wrong before shipping.
Python proficiency — clean, maintainable scripts for data transformation, normalization, and tooling (not just notebooks).
Experience with analytical or columnar databases — such as ClickHouse, BigQuery, Redshift, DuckDB, or similar.
Demonstrated experience building with an LLM API (Anthropic, OpenAI, or similar) — you understand tool use, structured outputs, and what it takes to make AI responses consistent and reliable.
Ability to work from well-defined requirements: translating a subject matter expert’s question into a data model and query that accurately answers it.
Comfort in a greenfield environment — able to make sound architectural decisions when patterns are still being established.
Familiarity with MCP (Model Context Protocol) or similar function-calling / tool-use patterns for LLMs (preferred).
What you will gain at Intapp
Our culture at Intapp emphasizes accountability, responsibility, and growth. We support each other in a positive, open atmosphere that fosters creativity, approachability, and teamwork. We’re committed to creating a modern work environment that’s connected yet flexible, supporting both professional success and work-life balance. In return for your passion, commitment, and collaborative approach, we offer:
Attractive compensation – including competitive base pay and performance-based variable pay.
Equity/Stock in Intapp.Opportunity to travel to other development centers for product training and cross-site collaboration.
One-time home office stipend.
Generous paid parental leave (including adoptive leave), marriage leave, bereavement leave, carer's leave, and paid sick days.
Reimbursement for training towards continuing education.
Intapp provides equal employment opportunities to all qualified applicants and will make hiring decisions without regard to race, color, sex, sexual orientation, gender identity or expression, religion, national origin or ancestry, age, disability, marital status, pregnancy, protected veteran status, protected genetic information, political affiliation, or any other characteristic protected by federal, state or local laws.
Please note: Intapp will not hire through text message, social media, or email alone. We will never extend a job offer unless you have been contacted directly by an Intapp recruiter and have participated in the interview process which will generally consist of 3 or more virtual or in person meetings. Please note that Intapp only uses company email addresses, which contain “@intapp.com” or “@dealcloud.com” to communicate with candidates via email. Intapp will never ask for financial information of any kind or for any payment during the job application process. We post all legitimate job openings on the Intapp Career Site at https://www.intapp.com/working-at-intapp/. If you believe you were a victim of such a scam, you may contact your local authorities. Intapp is not responsible for any claims, losses, damages, or expenses resulting from scammers.