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Asset Metadata Taxonomy Jobs in Silver Spring, MD

Review audio and catalog in media asset management system. * Provide metadata quality assurance on ... Maintain taxonomy standards by performing tag normalization in multiple systems. * Communicate best ...

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Asset Metadata Taxonomy information

See Silver Spring, MD salary details

$36.7K

$97.3K

$170.1K

How much do asset metadata taxonomy jobs pay per year?

As of Jul 28, 2026, the average yearly pay for asset metadata taxonomy in Silver Spring, MD is $97,309.00, according to ZipRecruiter salary data. Most workers in this role earn between $77,000.00 and $112,700.00 per year, depending on experience, location, and employer.

What are some common challenges faced by professionals working in Asset Metadata Taxonomy roles, and how can they be addressed?

Professionals in Asset Metadata Taxonomy often encounter challenges such as ensuring consistency across large and evolving datasets, integrating disparate metadata standards, and coordinating with multiple stakeholders like IT, content creators, and business units. Addressing these challenges typically involves establishing clear governance frameworks, utilizing robust taxonomy management tools, and maintaining open communication with cross-functional teams. Staying updated on industry best practices and regularly reviewing the taxonomy structure can also help prevent data silos and improve overall asset discoverability.

What is the difference between Asset Metadata Taxonomy vs Asset Data Analyst?

AspectAsset Metadata TaxonomyAsset Data Analyst
Primary FocusOrganizing and classifying asset metadataAnalyzing asset data for insights and reporting
Skills RequiredTaxonomy development, metadata standards, data managementData analysis, statistical skills, reporting tools
Work EnvironmentData management teams, information systemsBusiness units, analytics teams
CertificationsData management, taxonomy certificationData analysis, business intelligence certifications

While both roles involve working with asset data, Asset Metadata Taxonomy focuses on structuring and categorizing metadata for assets, whereas Asset Data Analysts interpret and analyze asset data to support decision-making. Understanding these differences helps organizations assign the right skills to each role.

What are the key skills and qualifications needed to thrive as an Asset Metadata Taxonomy Specialist, and why are they important?

To excel as an Asset Metadata Taxonomy Specialist, you need a strong background in information science, metadata standards, taxonomy development, and data organization, often supported by a degree in library science or a related field. Familiarity with content management systems (CMS), digital asset management (DAM) platforms, and metadata schema tools is essential. Attention to detail, analytical thinking, and effective communication are critical soft skills for collaborating with stakeholders and ensuring consistent taxonomy application. These skills ensure accurate asset classification, improve content discoverability, and support efficient information retrieval across digital platforms.

What is an Asset Metadata Taxonomy?

An Asset Metadata Taxonomy is a structured classification system used to organize and categorize digital assets, such as images, videos, documents, and other media, based on their descriptive metadata. This taxonomy helps organizations standardize the way they tag and retrieve assets, making it easier to search for and manage content efficiently. By defining categories, attributes, and relationships, an asset metadata taxonomy ensures consistency, improves discoverability, and supports effective digital asset management across teams and platforms.
What job categories do people searching Asset Metadata Taxonomy jobs in Silver Spring, MD look for? The top searched job categories for Asset Metadata Taxonomy jobs in Silver Spring, MD are:
What cities near Silver Spring, MD are hiring for Asset Metadata Taxonomy jobs? Cities near Silver Spring, MD with the most Asset Metadata Taxonomy job openings:

Data Governance Lead - Security Cooperation Data & Knowledge Management

Q2Impact

Arlington, VA โ€ข On-site

Full-time

Posted 12 days ago


Job description

Position Summary

The Data Governance Lead is responsible for establishing and managing the enterprise data governance framework supporting a Department of Defense (DoD) Security Cooperation platform. This role ensures that data across Security Cooperation programsโ€”including Foreign Military Sales (FMS), Building Partner Capacity (BPC), Institutional Capacity Building (ICB), International Military Education and Training (IMET), Humanitarian Assistance, and Security Cooperation workforce developmentโ€”is trusted, secure, discoverable, and actionable.

The Data Governance Lead will develop governance policies, data standards, metadata management, taxonomy, master data management, and lifecycle processes that enable secure information sharing, artificial intelligence (AI), advanced analytics, and enterprise knowledge management. Working across functional and technical teams, the incumbent will facilitate governance councils, promote data stewardship, and ensure compliance with DoD cybersecurity, records management, and data strategy requirements.

This position plays a critical role in transforming fragmented information into a strategic enterprise asset that supports decision-making, operational readiness, partner nation engagement, and institutional learning across the Security Cooperation enterprise.

Essential Duties and ResponsibilitiesEnterprise Data Governance
  • Develop and implement the enterprise Data Governance Framework for the Security Cooperation platform.
  • Establish governance policies, standards, procedures, and operating models aligned with DoD data strategies.
  • Lead governance activities that promote data quality, consistency, accessibility, and accountability.
  • Develop governance maturity roadmaps and implementation plans.
  • Facilitate cross-functional governance councils and working groups.
Data Stewardship
  • Identify and establish business and technical data steward roles across Security Cooperation organizations.
  • Define stewardship responsibilities and decision-making authorities.
  • Coordinate stewardship activities to resolve data ownership and quality issues.
  • Promote accountability for enterprise data assets.
Metadata & Taxonomy Management
  • Develop and maintain enterprise metadata standards.
  • Design and govern taxonomies, controlled vocabularies, ontologies, and tagging strategies.
  • Ensure consistent classification of operational, instructional, and programmatic content.
  • Support semantic search, AI-enabled discovery, and enterprise knowledge management.
Data Quality Management
  • Define enterprise data quality standards and performance metrics.
  • Develop processes for monitoring data completeness, consistency, validity, accuracy, and timeliness.
  • Lead root cause analysis and remediation of data quality issues.
  • Implement dashboards and scorecards for governance performance.
Knowledge Management Integration
  • Collaborate with Knowledge Management teams to improve discoverability and reuse of Security Cooperation knowledge.
  • Develop governance processes supporting AI-enabled search and enterprise knowledge repositories.
  • Standardize document classification and information architecture.
  • Enable organizational learning through structured information management.
Master and Reference Data Management
  • Establish governance for master data domains, including organizations, partner nations, personnel, programs, courses, authorities, funding sources, and capability areas.
  • Develop enterprise reference data standards.
  • Coordinate master data synchronization across systems.
Data Architecture Collaboration
  • Partner with enterprise architects and solution architects to align governance with technical architecture.
  • Review solution designs to ensure compliance with governance standards.
  • Support cloud-native data architectures within AWS environments.
  • Ensure governance requirements are incorporated into system development lifecycles.
AI Readiness & Information Management
  • Prepare enterprise information assets for Generative AI, machine learning, and advanced analytics.
  • Develop governance standards supporting Retrieval-Augmented Generation (RAG) architectures.
  • Ensure structured metadata supports AI search accuracy and transparency.
  • Establish governance for AI-generated content where appropriate.
Security & Compliance
  • Ensure compliance with the DoD Data Strategy, DoD Information Enterprise Architecture, Risk Management Framework (RMF), NIST SP 800-53, DoD Cloud Computing Security Requirements Guide (SRG), Federal Records Act, Controlled Unclassified Information (CUI) requirements, and information lifecycle management policies.
  • Coordinate with cybersecurity teams to ensure governance supports secure information sharing.
Stakeholder Engagement
  • Lead governance workshops with Security Cooperation stakeholders.
  • Build consensus across operational, educational, technical, and leadership communities.
  • Present governance recommendations to senior government leadership.
  • Develop governance documentation, policies, standards, and executive briefings.
Success Measures

Success in this role will be demonstrated by:

  • Establishing a sustainable enterprise Data Governance Program adopted across Security Cooperation organizations.
  • Improving data quality, consistency, and trust through measurable governance metrics.
  • Implementing standardized metadata and taxonomy that significantly enhance information discoverability.
  • Enabling AI-ready data and knowledge assets that support advanced search, analytics, and decision support.
  • Increasing reuse of institutional knowledge through improved governance and content lifecycle management.
  • Reducing duplicate, obsolete, and conflicting information across enterprise repositories.
  • Achieving compliance with DoD data governance, records management, and cybersecurity requirements.
  • Building an active network of data stewards who sustain governance practices across the enterprise.
Work Environment

The Data Governance Lead operates at the intersection of mission operations, enterprise technology, and organizational governance. This position requires collaboration with senior defense leaders, Security Cooperation practitioners, data architects, cybersecurity professionals, instructional designers, and knowledge management specialists to ensure that enterprise data is managed as a strategic asset.

The role is central to enabling data-informed decision-making, AI-enabled knowledge discovery, and enterprise interoperability across the Security Cooperation community while supporting the Department of Defense's broader digital modernization objectives.

Requirements

Required Qualifications
  • Hands-on experience establishing enterprise data governance and data stewardship models.
  • 2+ years of experience in enterprise data management, data governance, or information management.
  • Experience with AWS, Microsoft Purview, SharePoint Online, Power BI, and SQL.
  • Experience with core data governance practices, including data governance frameworks, metadata management, data cataloging, data quality management, Master Data Management (MDM), information lifecycle management, business glossaries, data lineage, and information lifecycle governance.
  • Experience facilitating governance councils or executive working groups.
  • Active Secret Security Clearance.
  • U.S. Citizenship and eligibility to work in the United States.
Preferred Qualifications
  • Bachelor's degree in Information Management, Data Science, Information Systems, Computer Science, Public Administration, International Relations, or a related field.
  • 5+ years supporting Department of Defense or Federal Government programs.
  • Experience supporting Security Cooperation organizations, including the Defense Security Cooperation Agency (DSCA), Geographic Combatant Commands, Military Departments, or Security Cooperation workforce development organizations.
  • Experience supporting Foreign Military Sales (FMS), Security Assistance, Institutional Capacity Building (ICB), or Building Partner Capacity (BPC) programs.
  • Knowledge of one or more governance standards or frameworks, including DoD Data Strategy, DoD Digital Modernization Strategy, Federal Data Strategy, DAMA-DMBOK, DCAM, or NIST data management guidance.
  • Preferred certifications include Certified Data Management Professional (CDMP), DAMA Certified Data Management Professional, Certified Information Professional (CIP), Security+, Certified Information Systems Security Professional (CISSP), or Prosci Change Management Certification.