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Metadata Analyst Jobs in Oklahoma (NOW HIRING)

$90K - $110K/yr

Build and maintain semantic models with rich metadata, business definitions, and synonyms to enable trusted self-service analytics and AI consumption. * Develop models that support multiple ...

... analyst, data analyst, product analyst) * Strong understanding of data concepts (data models, metadata, lineage, quality dimensions, master/reference data) * Ability to translate business ...

Fill out standardized metadata records detailing when spatial data was created, its source ... buffer analysis, and acreage calculations as directed. * Participate in GIS team projects ...

... analyst) • Strong understanding of data concepts (data models, metadata, lineage, quality dimensions, master/reference data) • Ability to translate business requirements into clear data ...

Data Engineer

Tulsa, OK · On-site

$104K - $125K/yr

Developing and maintaining SSIS-based ETL pipelines, including metadata-driven and dynamic ETL ... and analysis. A plus will be experience in AWS related to data engineering. Experience required ...

SEO Specialist

Oklahoma City, OK · Remote

$10 - $15/hr

... metadata formatting. * Keyword Integration: Strategically place target keywords, internal links, and image alt text into content according to project guidelines. * Search Intent Matching: Analyze ...

New

Establish and enforce data standards, naming conventions, and metadata governance. Manage platform ... Champion GIS adoption by identifying opportunities where spatial analysis can solve business ...

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Metadata Analyst information

See Oklahoma salary details

$28.6K

$67.6K

$120K

How much do metadata analyst jobs pay per year?

As of Jul 26, 2026, the average yearly pay for metadata analyst in Oklahoma is $67,644.00, according to ZipRecruiter salary data. Most workers in this role earn between $48,500.00 and $80,300.00 per year, depending on experience, location, and employer.

What is a Metadata Analyst job?

A Metadata Analyst is responsible for organizing, managing, and maintaining metadata—structured information about data—within an organization. They ensure that data assets are accurately categorized, labeled, and accessible, improving searchability and data governance. Their role often involves working with databases, content management systems, and metadata standards to enhance data quality and consistency. Additionally, they collaborate with IT, data management, and business teams to ensure metadata aligns with organizational goals.

Is 40 too old to become a data analyst?

Age is not a barrier to becoming a data analyst, as the role values skills in data manipulation, statistical analysis, and tools like Excel, SQL, and Python. Many professionals transition into data analysis later in their careers by gaining relevant certifications or training, regardless of age.

How much does a metadata analyst make?

A metadata analyst's salary typically ranges from $50,000 to $90,000 annually, depending on experience, location, and industry. Professionals with skills in data management tools and certifications may earn higher salaries, especially in larger organizations or tech-focused environments.

What kind of jobs in media bring in $150,000 a year?

In media, high-paying roles such as senior media analysts, media directors, or digital strategists can earn $150,000 or more annually. These positions often require extensive experience, advanced skills in data analysis or media planning, and proficiency with industry tools like analytics platforms or content management systems.

What are some typical challenges a Metadata Analyst might face in their daily work?

Metadata Analysts often encounter challenges such as managing large volumes of diverse data, ensuring metadata consistency across multiple systems, and navigating evolving data privacy regulations. Staying current with industry standards and adapting metadata frameworks to support new business needs can also be demanding. Working closely with IT, data governance, and business teams, Metadata Analysts must balance competing priorities and address data quality issues proactively. Overcoming these challenges helps enhance data findability, compliance, and overall organizational efficiency.

What are the key skills and qualifications needed to thrive in the Metadata Analyst position, and why are they important?

To thrive as a Metadata Analyst, a solid understanding of data management, database concepts, metadata standards, and a degree in information science, library science, or a related field is key. Familiarity with metadata management tools, data cataloging platforms, and systems like SQL, XML, and DAM (Digital Asset Management) systems, as well as certifications such as Certified Data Management Professional (CDMP), are often beneficial. Strong attention to detail, analytical thinking, and effective communication are essential soft skills that help with collaborating across departments. These combined skills ensure data is accurately organized, discoverable, and valuable for organizational decision-making and compliance.

What does a metadata analyst do?

A metadata analyst is responsible for organizing, managing, and analyzing metadata to improve data retrieval and usability. They often work with data management tools, ensure data quality, and develop standards for metadata documentation to support data governance and searchability.
What are popular job titles related to Metadata Analyst jobs in Oklahoma? For Metadata Analyst jobs in Oklahoma, the most frequently searched job titles are:
Infographic showing various Metadata Analyst job openings in Oklahoma as of July 2026, with employment types broken down into 69% Full Time, 6% Part Time, and 25% Contract. Highlights an 61% Physical, 5% Hybrid, and 34% Remote job distribution, with an average salary of $67,644 per year, or $32.5 per hour.
Analytics Engineer

$90K - $110K/yr

Other

Posted 17 days ago


Job description

Position Summary

The Analytics Engineer is responsible for owning the design, build, and ongoing maintenance of data products in the MART layer of the firm's data platform. This role creates and evolves foundational and business data products from governed underlying data, applying reusable business logic, documentation, testing, and access controls so data can be consumed consistently across the enterprise. The ideal candidate also authors and maintains semantic models that make trusted data easier to use for AI experiences, dashboards, reporting, and downstream integrations into operational platforms. Success in this role requires strong technical depth, a product mindset, and close partnership with engineering, BI, analytics, and business stakeholders.

This is a hybrid role with 3 days/week onsite in St. Louis.

Primary Responsibilities

  • Own the design, development, and maintenance of MART-layer foundational and business data products built from curated enterprise data.

  • Translate business requirements into reusable data products, metrics, and transformation logic that support consistent consumption across teams and platforms.

  • Build and maintain semantic models with rich metadata, business definitions, and synonyms to enable trusted self-service analytics and AI consumption.

  • Develop models that support multiple consumption patterns, including dashboards, reports, AI agents, APIs, file delivery, and operational system integrations.

  • Apply complex business logic in a governed, version-controlled manner using modern transformation tooling and software engineering best practices.

  • Partner with data engineers, BI engineers, analysts, architects, and business stakeholders to define product intent, validate logic, and prioritize enhancements.

  • Ensure data product quality through testing, monitoring, reconciliation, and issue resolution across upstream data, transformations, and downstream consumption.

  • Document data products, semantic models, lineage, and usage guidance to improve transparency, stewardship, and user adoption.

  • Support governed access patterns through metadata, role-based access considerations, and alignment with enterprise data governance standards.

  • Continuously improve MART-layer patterns, semantic model design, and consumer enablement based on platform evolution and business needs.

Required Skills

  • Strong experience building analytics-ready data models and reusable business logic in modern cloud data platforms such as Snowflake.

  • Hands-on expertise with DBT or similar transformation frameworks, including modular modeling, testing, documentation, and version control.

  • Proven ability to design and maintain semantic models, metrics, dimensions, and business definitions for consistent downstream consumption.

  • Strong SQL skills and experience optimizing transformation logic for performance, scalability, and maintainability.

  • Experience supporting multiple data consumption patterns, including BI dashboards, AI use cases, reporting, APIs, file delivery, and operational integrations.

  • Understanding of data governance, metadata, lineage, role-based access, and quality controls in enterprise data platforms.

  • Ability to partner effectively with cross-functional stakeholders to translate business needs into scalable, trusted data products.

  • Strong written and verbal communication skills with the ability to document logic, definitions, assumptions, and usage guidance clearly.

Qualifications

  • Bachelor's degree in Computer Science, Information Systems, Data Analytics, Engineering, or a related field, or equivalent practical experience.

  • 5+ years of experience in analytics engineering, data engineering, BI engineering, or a closely related data role.

  • Experience building governed data models and data products in enterprise environments with multiple downstream consumers.

  • Demonstrated experience applying software engineering best practices to analytics workflows, including Git-based development, testing, and deployment discipline.

  • Experience working with modern BI and semantic technologies such as Power BI, Snowflake semantic capabilities, or similar platforms is preferred.

  • Familiarity with metadata/catalog platforms, lineage tooling, and enterprise documentation practices is preferred.

  • Experience in financial services, wealth management, or other regulated industries is a plus.

  • Demonstrated ability to work independently, manage priorities, and take ownership of data products from design through ongoing support.

This position is an exempt position. The annualized base pay range for this role is expected to be between $90,000 - $110,000.  Actual base pay could vary based on factors including but not limited to experience, subject matter expertise, geographic location where work will be performed and the applicant's skill set.  The base pay is just one component of the total compensation package for employees.  Other reward may include an annual cash bonus and a comprehensive benefits package.

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