Partner Analytics & Operations Manager

Intapp•New York, NY

About The Position

Intapp is seeking a Partner Analytics & Operations Manager to shape how the company measures, scales, and evolves its partner ecosystem and to help build the AI capabilities that support it. Partners are central to Intapp’s platform and AI ambitions, particularly for customers in highly regulated industries. The role combines partner strategy, analytics, operational execution, and continuous development of AI-enabled tools. The manager will shape data architecture and performance measurement across more than 145 partnerships, own ecosystem reporting and dashboards, and provide analyses that inform partner selection, tiering, and commercial models. The role will also manage operations across the Data & Technology partner lifecycle, including program deployment, co-delivery, co-selling, performance tracking, and monetization. In collaboration with Product and teams across the company, the manager will help align partner activity and platform strategy. The position will advance partner ecosystem AI tools by prototyping and testing solutions, automating reporting and operations, and developing predictive signals for partner performance, co-sell opportunities, and emerging risks. The role is based in New York. Intapp describes its work environment as modern, connected, and flexible, with open offices designed for creativity and collaboration.

Requirements

At least 4 years of experience in analytics, data strategy, business operations, or a similar analytical role.
Ability to structure data, define metrics, reconcile discrepancies, identify trends, and create reporting that leadership trusts and uses.
Proficiency in Excel, BI tools, and data analysis techniques.
Comfort working with large datasets, formulas, and dashboards, and scripting data workflows when needed.
Ability to take end-to-end ownership, create structure in undefined areas, and make complex cross-functional processes clean and repeatable.
Strong attention to detail, including operational rigor in attribution, reporting accuracy, and process reliability.
Interest in using AI and automation to reduce manual work, improve data quality, and scale operations.
Ability to communicate with partner managers, sales, finance, product, and senior leadership, translating operational details into executive-ready narratives.

Nice To Haves

Management consulting background, including structured, hypothesis-driven problem solving, market framing, planning, and making evidence-based cases to executives.
Experience in partnerships, alliances, or channel management.
Familiarity with accounting, consulting, investment banking and advisory, legal, private capital, real assets, or professional services firms.
Applied AI fluency, including AI-enabled tooling, workflow automation, or building and deploying AI-assisted reporting and operational workflows.

Responsibilities

Shape data architecture, internal processes, measurements, definitions, and reporting across more than 145 partnerships.
Define and maintain the analytical logic for partner performance, including the versioning, approval, and communication of evolving definitions.
Own ecosystem-wide dashboards, weekly activity reports, pipeline rollups, and executive-ready materials, and automate their production.
Provide partner leadership with analyses to guide partner investment, tiering, and commercial models.
Implement, optimize, and maintain processes across the Data & Technology partner lifecycle, including program deployment, co-delivery, co-selling, performance tracking, and monetization models.
Own Data & Technology data-usage reporting and develop insights to optimize the portfolio and drive revenue growth.
Support analytics that align Data & Technology partners with Product and coordinate work across sales, marketing, services, IT, legal, and finance.
Continuously innovate partner ecosystem AI tools by prototyping solutions, testing them with colleagues, and refining or discontinuing them based on results.
Develop predictive signals for partner performance, co-sell opportunities, and emerging risks.
Help establish reliable AI standards and contribute to the AI tools roadmap.