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Data Intelligence Manager Jobs in Tennessee (NOW HIRING)

Mars

Sr. Manager Enterprise Intelligence

Franklin, TN · On-site

Are you ready to shape the future of data, analytics, and AI for some of the world's most beloved ... Experience: 7+ years of progressive experience in data management, analytics, business intelligence ...

kgs

Intelligence Analyst

Nashville, TN · On-site

... data from multiple sources into actionable intelligence. * Proficiency in open-source intelligence (OSINT) research methods and tools. * Experience with law enforcement records management systems and ...

Koniag, Inc.

Intelligence Analyst

Nashville, TN · On-site

... data from multiple sources into actionable intelligence. * Proficiency in open-source intelligence (OSINT) research methods and tools. * Experience with law enforcement records management systems and ...

kgs

Intelligence Analyst

Nashville, TN · On-site

... data from multiple sources into actionable intelligence. * Proficiency in open-source intelligence (OSINT) research methods and tools. * Experience with law enforcement records management systems and ...

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Data Intelligence Manager information

What are the key skills and qualifications needed to thrive as a Data Intelligence Manager?

To thrive as a Data Intelligence Manager, you need expertise in data analytics, business intelligence, and data management, typically supported by a degree in computer science, statistics, or a related field. Familiarity with BI tools like Tableau or Power BI, data warehousing solutions, and certifications such as Certified Analytics Professional (CAP) are highly beneficial. Strong leadership, strategic thinking, and communication skills are essential for effectively guiding teams and translating complex data insights into actionable strategies. These skills ensure the effective transformation of raw data into valuable business insights, driving informed decision-making and organizational growth.

How does a Data Intelligence Manager typically collaborate with cross-functional teams within an organization?

A Data Intelligence Manager often works closely with teams such as IT, business operations, marketing, and product development to ensure that data-driven insights align with organizational goals. This role requires facilitating clear communication between data analysts, engineers, and non-technical stakeholders to translate complex data findings into actionable strategies. Regular meetings, project updates, and cross-department workshops are common, fostering a collaborative environment where data initiatives support business objectives. Building strong relationships across teams is essential for driving successful data intelligence projects.

What is the difference between Data Intelligence Manager vs Data Analyst?

AspectData Intelligence ManagerData Analyst
Required CredentialsBachelor's or Master's in Data Science, Analytics, or related field; often certifications in data toolsBachelor's in Statistics, Mathematics, or related field; certifications in data analysis tools are common
Work EnvironmentLeads teams, manages data strategies, collaborates with stakeholdersAnalyzes data sets, prepares reports, supports decision-making
Employer & Industry UsageUsed in corporate, tech, finance sectors for strategic data rolesCommon across various industries for operational data analysis

The Data Intelligence Manager focuses on leading data strategies and managing teams, while the Data Analyst primarily analyzes data to support business decisions. Both roles require strong analytical skills and familiarity with data tools, but differ in scope and responsibilities.

What does a data intelligence manager do?

A data intelligence manager oversees the collection, analysis, and interpretation of data to support business decision-making. They develop data strategies, manage data teams, and use tools like SQL, data visualization software, and analytics platforms to turn data into actionable insights.

What cities in Tennessee are hiring for Data Intelligence Manager jobs?

Cities in Tennessee with the most Data Intelligence Manager job openings:

Infographic showing various Data Intelligence Manager job openings in Tennessee as of August 2026, with employment types broken down into 88% Full Time, 11% Part Time, and 1% Contract. Highlights an 84% Physical, 3% Hybrid, and 13% Remote job distribution.

Director, Product Management - Data Intelligence Foundation

Relativity

Nashville, TN • On-site

Other

Re-posted 14 hours ago

Job description

Posting Type

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 Requirements

Whatyou'llown

The 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 canbuild onwith confidence. The underlying data primitives are the foundation; the degree to which the retrieval layer (Query Plane) matches this structuredetermineshow easily the organization can navigate between "slow data" and "fast data" use cases.

  • Ontology / Relationship: The semantic layer of the Relativity Intelligence Model. Ontology encodesmeaning: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+ yearsleading 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 API contract, contribute to engineering scope decisions, and articulate the trade-offs in a data consistency model.

  • Demonstrated ability to manage and build a PM team through hiring, leveling, and establishing product practice for a new domain

  • Bachelor's degree in Business, Computer Science, Engineering, or Design, or comparable work experience

Preferred qualifications

  • Experience building at companies where the data platform is the product, not a supporting system.Snowflake, Databricks, Elastic, MongoDB, Palantir, and similar are strong indicators of the right background.

  • Experience building for AI systems, agents, or ML pipelines as primary consumers. You understand what a model needs from data that a humandoesn't, and you design for both.

Ways of working

  • Engineering credibility is paramount.You will be in technical discussions with skilled and knowledgeable engineering leaders regularly.You need to be a peer in those conversations, not a relay.

  • Organizational cadence.Youestablishthe operating rhythm for a multi-pillar PM org: the forum structure, planning cadence, and decision frameworks that let the team move with velocity and alignment. When priorities conflict across pillars, you hold the trade-off clearly and resolve it cleanly.

  • Internal GTM ownership.Adoption of the Foundational Layer means every product team at Relativity builds with it. You define how internal teams discover, integrate, and get value from platform services, and you measure it. This is a product strategy job and a change management job simultaneously.

  • Coaching a scaling PM org.You build PM capability, not just PM headcount, leveling people up while running at speed.

  • Cross-functional influence without authority.Youdon'tcontrol the teams that need to adopt what you build. You make the new path clearly better and bring teams along through clarity, evidence, and trust.

  • Directional clarity under ambiguity.Several of these primitives are being defined as the engineering teams build. You make good decisions with incomplete information and update them whenrequired.

  • Legal domain expertise is notrequired.However, internalizing why defensibility, chain of custody, and auditability are first-class design requirements.

Relativity is committed to competitive, fair, and equitable compensation practices.

This position is eligible for total compensation which includes a competitive base salary, an annual performance bonus, and long-term incentives.

The expected salary range for this role is between following values:

$188,000 and $282,000

The final offered salary will be based on several factors, including but not limited to the candidate's depth of experience, skill set, qualifications, and internal pay equity. Hiring at the top end of the range would not be typical, to allow for future meaningful salary growth in this position.

Required Skills:

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