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Data Intelligence Manager Jobs in Utah (NOW HIRING)

Manager Data Intelligence

Draper, UT · On-site

$150 - $200/hr

Manager Data Intelligence (Draper, UT, In‑Office) About the Position We are seeking an experienced and technically strong Data, Knowledge, and Intelligence Manager to lead the planning, design ...

Manager Data Intelligence (Draper, UT, In-Office) Upbound Group, Inc. (NASDAQ: UPBD) is a technology and data-driven leader in accessible and inclusive financial solutions that address the evolving ...

Harris Williams is seeking an Oracle ERP / Fusion Data Intelligence Reporting Analyst to support financial, operational, and management reporting across Oracle ERP Cloud, Oracle Fusion Data ...

... data intelligence, providing enterprise-grade SaaS solutions for address validation, geocoding, and data enrichment. The Digital Analytics Specialist will manage analytics instrumentation, configure ...

Senior Product Manager

Orem, UT · On-site

$110K - $145K/yr

They are seeking a Senior Product Manager to contribute to product strategy and partner with ... The leader in location data intelligence. Smarty's APIs verify, validate, enrich, standardize ...

IT Data Scientist

Bluffdale, UT · On-site

$150 - $200/hr

... intelligence stakeholders and in compliance with technical and architectural standards. This ... and product managers to turn data analysis into actionable algorithms Champion a data-driven ...

UT · On-site

... manage their Gross to Net deductions, recovering additional funds on their behalf. We work within our customers' existing ERP ecosystem and help them integrate data intelligence from a variety of ...

Senior Product Manager

Orem, UT · On-site

$130K - $160K/yr

We have an immediate opportunity for a Senior Product Manager to join our team. This is a great ... AI and ML can improve data quality and product intelligence * A strong cross-functional ...

$83K - $109K/yr

Communicates with other intelligence departments and agencies to share data and techniques, findings, and planning for future operations. * Geospatial (GI&S) Program Manager for the unit. Creates and ...

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Showing results 1-20

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 Utah are hiring for Data Intelligence Manager jobs?

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

Infographic showing various Data Intelligence Manager job openings in Utah 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.

Manager Data Intelligence

Upbound Group Inc.

Draper, UT • On-site

$150 - $200/hr

Other

Medical, Dental, Vision, Retirement

Re-posted 2 days ago


Job description

Manager Data Intelligence

(Draper, UT, In‑Office)

About the Position

We are seeking an experienced and technically strong Data, Knowledge, and Intelligence Manager to lead the planning, design, development, and delivery of enterprise data intelligence products. This role acts as the bridge between business stakeholders, product managers, and engineering teams by translating business needs into scalable data solutions. The ideal candidate combines strong data architecture, technical leadership, experience in enterprise data products management, familiarity with Generative AI, LLMs, and agentic AI concepts, and Agile delivery skills to ensure high‑quality, dependable, and scalable data intelligence products.

Data Intelligence Roadmaps & Stakeholder Management
  • Partner with business VPs, Directors, users, product managers, and leadership teams to understand business needs and develop use cases and requirements for enterprise data, knowledge, and intelligence products.
  • Facilitate requirement discovery workshops and stakeholder discussions.
  • Drive alignment between business priorities and data product roadmaps.
  • Evaluate and prioritize Generative AI, predictive analytics, machine learning, and intelligent automation use cases.
  • Act as the primary liaison between business and data/technical teams.
  • Translate roadmaps, business use cases, and requirements into actionable deliverables and guide the creation of clear functional and technical specifications.
Analytics & Insights Enablement
  • Deliver trusted data and intelligence products and self‑service capabilities to business users.
  • Enable data‑driven decision‑making through dashboards, insights, and AI‑powered capabilities and solutions.
  • Promote data literacy and AI adoption across the organization.
Data Architecture & Solution Design
  • Define and provide architecture and solution guidance for enterprise data, knowledge, and intelligence products.
  • Ensure solutions align with established data architecture standards, design patterns, and engineering frameworks.
  • Review solution designs to ensure scalability, performance, governance, security, and reusability.
  • Collaborate with architects and engineering teams to establish best practices and technical standards.
Data Intelligence Products Backlog Ownership & Delivery
  • Develop and manage product backlogs, roadmaps, and release plans; act as the de‑facto portfolio/product manager and create/manage Jira epics, features, user stories, tasks, and acceptance criteria based on business requirements.
  • Prioritize features based on business value, customer impact, and strategic alignment; define product requirements, user stories, acceptance criteria, and success metrics.
  • Lead sprint planning, backlog grooming, sprint reviews, and retrospectives.
  • Ensure requirements are clearly documented and understood by development teams.
  • Monitor project progress and proactively manage risks, dependencies, and escalations.
Data Governance & Quality
  • Ensure data products comply with regulatory, privacy, security, and compliance requirements.
  • Drive metadata management, data lineage, cataloging, and discoverability initiatives.
  • Leverage AI where possible to implement data governance capabilities and solutions.
  • Monitor and improve data reliability, accuracy, consistency, and trustworthiness.
Resource Planning & Capacity Management
  • Develop quarterly resource and capacity plans based on current project commitments, strategic priorities, and future demand.
  • Evaluate team utilization and forecast staffing requirements.
  • Partner with leadership to prioritize work and optimize resource allocation.
  • Support budget planning and workforce planning activities.
Technical Leadership & Quality Assurance
  • Conduct architecture, design, and code reviews to ensure adherence to standards and best practices.
  • Verify the quality, performance, reliability, and maintainability of data products.
  • Drive implementation of data quality, testing, monitoring, and operational excellence practices.
  • Establish and enforce coding standards, development frameworks, and governance processes.
Leadership & Innovation
  • Foster a culture of experimentation, innovation, and AI‑driven problem solving.
  • Mentor teams on product thinking, data strategy, and AI best practices.
  • Stay current on industry trends, emerging technologies, and competitive developments.
  • Drive enterprise‑wide AI and data product transformation initiatives.
  • Lead daily stand‑up meetings and coordinate cross‑functional team activities.
  • Provide mentorship and technical guidance to data engineers and developers.
  • Foster a culture of continuous improvement and knowledge sharing.
  • Facilitate collaboration across engineering, architecture, product management, and business teams.
Escalation Management & Technical Troubleshooting
  • Serve as the technical escalation point for critical production issues and complex data challenges.
  • Perform direct troubleshooting and root‑cause analysis when necessary.
  • Guide teams through issue resolution and implementation of preventative measures.
  • Support production deployments and operational readiness activities.
Required Qualifications
  • 15 years in data, analytics, engineering, data architecture, data product management, or related roles.
  • 5+ years leading enterprise data products or AI‑enabled products.
  • Experience building AI, analytics, or data products/platforms at scale.
  • Demonstrated success delivering measurable business value from data and intelligence products.
  • Strong experience gathering and documenting business requirements.
  • Experience creating and managing Jira stories, epics, and Agile backlogs.
  • Strong understanding of data architecture, data modeling, and data integration patterns.
  • Experience reviewing code and enforcing engineering best practices.
  • Excellent communication, leadership, stakeholder management, and problem‑solving skills.
  • Ability to balance strategic planning with hands‑on technical execution.
  • Bachelor’s degree in computer science, information systems, data engineering, or a related field.
  • Knowledge of data warehouse, lakehouse, and data mesh architectures.
  • Familiarity with platforms such as Snowflake, Databricks, or similar technologies.
Required Skills
  • Business value realization
  • Stakeholder management and executive communication
  • Data strategy and governance
  • Data architecture and data modeling (dimensional and relational)
  • Experience implementing AI solutions; preferred experience with Generative AI, Agentic AI, Retrieval‑Augmented Generation, Knowledge Graphs, Vector Databases, Semantic Search, Prompt Engineering, and AI product management
  • Data product management
  • Business requirements gathering
  • Agile/Scrum methodologies
  • Jira backlog management
  • Enterprise data warehousing
  • Snowflake and cloud data warehouses
  • Python
  • SQL
  • ETL/ELT design and development
  • Data quality and data governance
  • Code reviews and quality assurance
  • Production support and technical troubleshooting
  • Performance tuning and optimization
  • Resource planning and capacity management
  • CI/CD and DevOps practices
Compensation & Benefits
  • Full health benefits – Medical, Dental, Vision
  • 401(k) match, 6%/3%
  • Discretionary time off (DTO)
  • Health savings account (HSA) with company contribution
  • College tuition reimbursement program (STEM degrees)
  • Unlimited access to LinkedIn Learning
  • Free car charging
  • On‑site gym and showers
Spousal Sponsorship

Applicants must be authorized to work for any employer in the U.S. We are unable to sponsor or take over sponsorship of an employment visa at this time.

Equal Opportunity Employment

Upbound, Acima, and Brigit are equal‑opportunity employers committed to ensuring that all employment decisions are made on a non‑discriminatory basis, and without regard to actual or perceived race.

Join Us

Join us at the forefront of digital innovation, where your work will directly impact the future of financial accessibility and consumer experiences across retail, ecommerce, and fintech.

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