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Product Data Intelligence Manager Jobs (NOW HIRING)

Pinkerton

Intelligence Manager

Foster City, CA · On-site

$140K - $150K/yr

The Intelligence Manager, assigned to a specific client, will play a pivotal role in managing the ... The Manager oversees a team of Analysts who provide best-in-class analytical products and expertise ...

Zillow

Principal Business Intelligence Manager

$143K - $229K/yr

You set the business architecture, semantic standards, data-product direction, and source-of-truth ... Mentor senior Business Intelligence Managers, analysts, and analytics engineers by shaping the ...

Zillow

Principal Business Intelligence Manager

$143K - $229K/yr

You set the business architecture, semantic standards, data-product direction, and source-of-truth ... Mentor senior Business Intelligence Managers, analysts, and analytics engineers by shaping the ...

Data Intelligence LLC

Senior Data Analyst

Quantico, VA · On-site

$91K - $114K/yr

Data Intelligence LLC Job Openings >> Senior Data Analyst Senior Data Analyst Summary Title: Senior ... Build and manage ETL pipelines for ingesting, transforming, and delivering structured and ...

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Product Data Intelligence Manager information

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$51.5K

$159.4K

$197K

How much do product data intelligence manager jobs pay per year?

As of Sep 11, 2026, the average yearly pay for product data intelligence manager in the United States is $159,405.00, according to ZipRecruiter salary data. Most workers in this role earn between $141,000.00 and $197,000.00 per year, depending on experience, location, and employer.

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Infographic showing various Product Data Intelligence Manager job openings in the United States as of August 2026, with employment types broken down into 88% Full Time, 11% Part Time, and 1% Contract. Highlights an 85% Physical, 2% Hybrid, and 13% Remote job distribution, with an average salary of $159,405 per year, or $76.6 per hour.

Director, Product Management - Data Intelligence Foundation (Wichita)

Wichita, KS • On-site

Relativity
See more jobs at Relativityexternal

Full-time

This job post has expired 2 days ago. Applications are no longer accepted.

Key responsibilities

  • Own the full product management layer across multiple engineering organizations for the Data Intelligence Foundation, including defining and managing data primitives such as Files, Ontology, Data Capabilities, Knowledge/Metadata, and Query Plane.

  • Define and oversee the development of data primitives to ensure they support reliable, accessible, and performant legal data storage, reasoning, and retrieval across all AI applications and workflows.

  • Drive the product roadmap and coordinate with engineering teams to build and enhance the foundational data platform components critical for legal data intelligence.

Job description

Remote/Hybrid

Job Overview

Relativity is a leading legal data intelligence company building AI technology that helps organizations organize data, discover the truth, and act on it with confidence. Over two decades, the company has built the most trusted platform in legal data, earning deep relationships with the world's leading law firms, corporations, and government agencies, and managing petabytes of the most sensitive data in existence. That foundation is now being turned into something larger: The AI platform for legal data intelligence. The Relativity Intelligence Model is the architecture for that transformation. At its base is the Foundational Layer (Relativity's shared data platform serving all AI applications). Five primitives give AI agents the structure, meaning, and retrieval capability they need to reason over legal data at scale: Files, Ontology, Data Capabilities, Knowledge/Metadata, and Query Plane. Relativity's Data Intelligence Foundation engineering org is building this layer. The product leadership that shapes it, drives adoption across Relativity's product teams, and builds the PM discipline to own it long-term. That's this role. The Director of Product Management, Data Intelligence Foundation is one of the highest-leverage product roles at Relativity. The Foundational Layer is what makes every Relativity aiR application smarter, every agent more reliable, and every Relativity product team faster. Getting it right matters enormously.

Job Description and RequirementsWhat you’ll ownThe full PM layer across multiple engineering orgs

  • Files / Natives: The storage primitive for legal documents, images, and native files. You define the substrate that makes immutable legal data consistently accessible across every product, partner integration, and AI workflow, with the SLAs, access contracts, and API surface that teams can build on with confidence. The underlying data primitives are the foundation; the degree to which the retrieval layer (Query Plane) matches this structure determines how easily the organization can navigate between slow data and fast data use cases.

  • Ontology / Relationship: The semantic layer of the Relativity Intelligence Model. Ontology encodes meaning: what kinds of things exist in legal data and how they relate, so that AI agents can reason, not just query. You define what Relativity's Ontology becomes: the entities, relationships, and contracts that give every Skill and Agent a shared vocabulary for legal data.

  • Data Capabilities: Reporting, Audit, and internal data infrastructure. The operational backbone that makes the platform observable, auditable, and explainable. These are non-negotiable properties in legal data intelligence use cases.

  • Knowledge / Metadata: The core data model that every product team, customer, and integration partner works with. A unified materialized document layer, consistent across all workspaces, is the mandate. Your roadmap evolves this surface to serve AI application teams as first-class consumers alongside the users who have relied on it for years.

  • Query Plane: One of the most performance-sensitive and strategically important services in the product. The mandate is a unified retrieval pillar with a rich materialized document layer: standardized ingestion APIs independent of data source, hybrid retrieval (lexical + vector) with reranking, chunking as a managed capability, and tiered storage (cold/warm/hot).

Minimum qualifications

  • 12+ years in product management; 5+ years leading platform or infrastructure PM organizations

  • Deep fluency with data platform primitives, including storage systems, metadata layers, knowledge graphs, query engines, or equivalent. You can design an

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