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Metadata Manager Jobs in Utah (NOW HIRING)

Manage business glossary in collaboration with business teams and build/maintain technical metadata for assigned data domains. * Define data quality rules and controls for assigned data domains and ...

Complete image processing, file organization, and metadata management tasks * Follow established SOPs and communicate quality concerns or process improvement ideas to Leads * Collaborate with ...

Complete image processing, file organization, and metadata management tasks * Follow established SOPs and communicate quality concerns or process improvement ideas to Leads * Collaborate with ...

Complete image processing, file organization, and metadata management tasks * Follow established SOPs and communicate quality concerns or process improvement ideas to Leads * Collaborate with ...

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Metadata Manager information

See Utah salary details

$25K

$74.4K

$125.2K

How much do metadata manager jobs pay per year?

As of Jun 30, 2026, the average yearly pay for metadata manager in Utah is $74,356.00, according to ZipRecruiter salary data. Most workers in this role earn between $45,500.00 and $106,100.00 per year, depending on experience, location, and employer.

What is the difference between Metadata Manager vs Data Analyst?

AspectMetadata ManagerData Analyst
Required CredentialsBachelor's degree in Information Science, Data Management, or related field; certifications like CDMPBachelor's degree in Statistics, Data Science, or related field; certifications like CAP or Microsoft Data Analyst
Work EnvironmentData management teams, IT departments, data governance officesBusiness units, analytics teams, reporting departments
Employer & Industry UsageUsed in organizations with large data repositories, data governance, and compliance needsUsed across industries for data-driven decision making, reporting, and insights

While both roles involve working with data, a Metadata Manager focuses on organizing, maintaining, and ensuring the quality of metadata to improve data accessibility and governance. A Data Analyst interprets data to generate insights and support business decisions. Understanding these differences helps organizations assign the right roles for their data needs.

How does a Metadata Manager typically collaborate with other departments within an organization?

A Metadata Manager frequently works cross-functionally with departments such as IT, data governance, business intelligence, and compliance to ensure consistent data definitions and standards. This role involves facilitating communication between technical teams and business stakeholders to align data cataloging practices with organizational goals. Metadata Managers often lead training sessions, develop documentation, and help teams understand the importance of metadata quality, making collaboration and strong interpersonal skills key parts of the job.

What are the key skills and qualifications needed to thrive as a Metadata Manager, and why are they important?

To thrive as a Metadata Manager, you need strong expertise in data management, metadata standards, taxonomy, and information architecture, typically supported by a related degree in library science, information management, or computer science. Familiarity with metadata management tools (e.g., Collibra, Informatica), data catalog systems, and knowledge of data governance frameworks is essential. Attention to detail, analytical thinking, and effective communication are critical soft skills for collaborating with stakeholders and ensuring data quality. These skills and qualifications are crucial for organizing, standardizing, and maximizing the value of organizational data assets.

What are Metadata Managers?

Metadata Managers are professionals responsible for organizing, maintaining, and overseeing the metadata that describes data assets within an organization. Their role ensures that information about data—such as its source, format, ownership, and usage—is accurately recorded and easily accessible. This helps improve data governance, enables efficient data retrieval, and supports compliance with data regulations. Metadata Managers often collaborate with IT, data governance, and business teams to implement metadata standards and tools.
What are the most commonly searched types of Metadata jobs in Utah? The most popular types of Metadata jobs in Utah are:
What are popular job titles related to Metadata Manager jobs in Utah? For Metadata Manager jobs in Utah, the most frequently searched job titles are:
What cities in Utah are hiring for Metadata Manager jobs? Cities in Utah with the most Metadata Manager job openings:
Infographic showing various Metadata Manager job openings in Utah as of June 2026, with employment types broken down into 2% As Needed, 6% Full Time, 82% Part Time, 2% Temporary, 7% Contract, and 1% Nights. Highlights an 83% Physical, 3% Hybrid, and 14% Remote job distribution, with an average salary of $74,356 per year, or $35.7 per hour.
Data Engineer IV - AI & Data Products

Data Engineer IV - AI & Data Products

Upbound

Draper, UT

$107K - $128K/yr

Other

Medical, Dental, Vision, Retirement

Posted 11 days ago


Job description

Data Engineer IV - AI & Data Products

(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 needs and aspirations of underserved customers. The Company's customer-facing operating units include industry-leading brands such as Acima, Brigit, and Rent-A-Center that facilitate consumer transactions across a wide range of store-based and digital channels, including over 2,300 company branded retail units across the United States, Mexico, and Puerto Rico. Upbound Group, Inc. is headquartered in Plano, Texas.

KEY RESPONSIBILITIES

Data Products & Data Integration

  • Define, build, validate and maintain domain-specific data product assets and data pipelines.

  • Collaborate with analytics and business partners to define and build semantic layers/models to support various personas - Report consumers, Self-Service and Advanced SQL Analysts, Data Scientists and AI use cases/agents.

  • Create and maintain data domain assets (pipelines/ETLs, sematic models and other assets) using Python, SQL, and other approved tools.

  • Build high quality solutions and assets aligned to defined architectural guidelines, data integration patterns, frameworks, and tools.

  • Build solutions aligned to security, risk, and compliance guidelines.

  • Support analysts and product teams with data products and assigned data domain expertise.

  • Assemble large complex data sets that meet functional/non-functional business requirements.

  • Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery and re-designing infrastructure for greater scalability.

  • Perform data analysis required to troubleshoot data related issues and assist in the resolution of data issues.

Data Governance & Quality

  • Manage business glossary in collaboration with business teams and build/maintain technical metadata for assigned data domains.

  • Define data quality rules and controls for assigned data domains and data assets (consumption, gold, silver, bronze layer tables).

  • Validate domain datasets for accuracy and completeness. Ensure domain data is of high quality and consumable by reporting, analytics, data science, and AI use cases.

Stakeholder Collaboration

  • Collaborate with business leaders, Executives, Data Scientists, BI Analytics, Product, Engineering, and other operational departments to ensure successful delivery of data solutions and data assets (consumption, gold, silver, bronze layer tables)

  • Translate business requirements into Data Products and data assets (consumption, gold, silver, bronze layer tables & pipelines) build specifications.

SKILLS, EXPERIENCES & QUALIFICATIONS

  • 8+ years of experience in Data Engineering roles

  • 2+ years of warehouse data modeling and pipeline design experience

  • Experience with data warehousing: Snowflake or similar systems

  • Strong Python experience

  • Strong SQL experience

  • Strong REST API experience

  • Experience using Linux.

  • Ability and motivation to learn new technologies quickly with minimal support and guidance.

  • Strong communication skills

  • Experience supporting and working with cross-functional teams in a dynamic environment.

Additional Experience:

  • AI-Driven Data Engineering Mindset - Hands-on experience using AI-assisted development tools (e.g., Copilot, generative AI) to accelerate pipeline design, code generation, and troubleshooting.

  • Intelligent Pipeline Development - Ability to design pipelines that incorporate AI for data transformation, anomaly detection, data classification, and schema evolution.

  • AI-Enabled Data Quality & Observability - Experience using AI/ML techniques for automated data quality checks, root cause analysis, and proactive monitoring.

Metadata & Semantic Layer Enrichment - Ability to use AI to auto-generate metadata, data documentation, semantic mappings, and business glossary entries

COMPENSATION/BENEFITS

  • Full health benefits-Medical/Dental/Vision

  • 401(k) match, 6%/3%

  • DTO (discretionary time off)

  • Health savings account (HSA) with company contribution

  • College tuition reimbursement program (STEAM degrees)

  • Unlimited use of Linkedin Learning

  • Free car charging

  • Onsite gym and showers

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 visaat this time.

Upbound is an equal opportunity employer committed to ensuring that all employment decisions are made on a non-discriminatory basis, and without regard to actual or perceived race.