ZipRecruiter

Log In

1

Metadata Jobs in Vermont (NOW HIRING)

TriOptus LLC

DataOps Engineer

Montpelier, VT · On-site

$115K - $139K/yr

Define and maintain metadata standards, data glossary entries, and end-to-end data lineage * Establish governance procedures, SOPs, and disclosure/suppression rules * Translate downstream analytics ...

Trioptus

DataOps Engineer

Montpelier, VT · On-site

Define and maintain metadata standards, data glossary entries, and end‑to‑end data lineage * Establish governance procedures, SOPs, and disclosure/suppression rules * Translate downstream ...

Trioptus

DataOps Engineer

Montpelier, VT · Remote

... metadata standards, data glossary entries, and end to end data lineage Establish governance procedures, SOPs, and disclosure/suppression rules Translate downstream analytics and governance ...

Trioptus

DataOps Engineer

Montpelier, VT · Remote

... metadata standards, data glossary entries, and end to end data lineage Establish governance procedures, SOPs, and disclosure/suppression rules Translate downstream analytics and governance ...

RSM

TESS Intern - Fall 2026

Barre, VT

$14.75 - $19.75/hr

Developing data and storage requirements, reporting, analytics, and delivery methods in data standards and metadata. * Develop, analyze, and evaluate data to create and maintain business intelligence ...

RSM

TESS Intern - Fall 2026

Colchester, VT

$15 - $20/hr

Developing data and storage requirements, reporting, analytics, and delivery methods in data standards and metadata. * Develop, analyze, and evaluate data to create and maintain business intelligence ...

RSM

TESS Intern - Fall 2026

Essex Junction, VT

$15.25 - $20.25/hr

Developing data and storage requirements, reporting, analytics, and delivery methods in data standards and metadata. * Develop, analyze, and evaluate data to create and maintain business intelligence ...

RSM

TESS Intern - Fall 2026

Montpelier, VT

$15.25 - $20.25/hr

Developing data and storage requirements, reporting, analytics, and delivery methods in data standards and metadata. * Develop, analyze, and evaluate data to create and maintain business intelligence ...

RSM

TESS Intern - Fall 2026

Burlington, VT

$14.75 - $19.75/hr

Developing data and storage requirements, reporting, analytics, and delivery methods in data standards and metadata. * Develop, analyze, and evaluate data to create and maintain business intelligence ...

RSM

TESS Intern - Fall 2026

Rutland, VT

$15.25 - $20.50/hr

Developing data and storage requirements, reporting, analytics, and delivery methods in data standards and metadata. * Develop, analyze, and evaluate data to create and maintain business intelligence ...

All JobsMetadata JobsMetadata Jobs in Vermont

Metadata information

See Vermont salary details

$8

$16

$30

How much do metadata jobs pay per hour?

As of Jun 8, 2026, the average hourly pay for metadata in Vermont is $16.73, according to ZipRecruiter salary data. Most workers in this role earn between $12.50 and $18.65 per hour, depending on experience, location, and employer.

What is the difference between Metadata vs Data Analyst?

AspectMetadataData Analyst
Required CredentialsKnowledge of data management, basic understanding of databasesBachelor's degree in statistics, data science, or related field
Work EnvironmentData management teams, IT departmentsBusiness, finance, marketing teams
Employer & Industry UsageUsed across industries for data catalogingUsed in analytics, reporting, decision-making
Common Search & ComparisonUnderstanding data structureAnalyzing data for insights

Metadata involves managing data about data, such as descriptions and structure, while a Data Analyst interprets data to provide insights. Both roles are essential in data management but serve different functions within organizations.

What are metadata specialists?

Metadata specialists are professionals responsible for creating, managing, and maintaining metadata, which is data that describes and provides information about other data. They work to ensure that digital assets, documents, or datasets are accurately categorized, searchable, and retrievable by assigning standardized descriptions and tags. Metadata specialists often work in libraries, archives, museums, or organizations with large digital collections, and play a key role in data governance and information management.

What are 5 examples of metadata?

Metadata for a Metadata professional refers to data that describes other data, such as file size, creation date, author, file format, and keywords. These examples help organize, find, and manage digital information efficiently. Understanding and managing metadata is essential in data management, digital archiving, and information retrieval tasks.

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

To thrive as a Metadata Specialist, you need strong organizational skills, attention to detail, and knowledge of metadata standards and cataloging principles, often supported by a degree in library science, information science, or a related field. Familiarity with cataloging tools, metadata management systems, and standards like Dublin Core or MARC is typically required. Excellent communication, problem-solving abilities, and collaboration skills help you work effectively with cross-functional teams and stakeholders. These skills ensure accurate data organization and retrieval, which are critical for maintaining data integrity and supporting information discovery.

What are some typical challenges faced by metadata specialists when managing large datasets, and how can they be addressed?

Metadata specialists often encounter challenges such as inconsistent data standards, incomplete metadata entries, and integrating metadata from multiple sources. These issues can make it difficult to ensure data discoverability and usability. Addressing them typically involves establishing clear metadata standards, using automated tools for validation, and collaborating closely with data owners and IT teams to maintain consistency. Regular training and documentation updates also help in keeping metadata practices aligned across the organization.
What are the most commonly searched types of Metadata jobs in Vermont? The most popular types of Metadata jobs in Vermont are:
What job categories do people searching Metadata jobs in Vermont look for? The top searched job categories for Metadata jobs in Vermont are:
Metadata jobs near you
Infographic showing various Metadata job openings in Vermont as of May 2026, with employment types broken down into 94% Full Time, 1% Part Time, and 5% Contract. Highlights an 82% Physical, 5% Hybrid, and 13% Remote job distribution, with an average salary of $34,802 per year, or $16.7 per hour.
Semantic Data Engineer | Digital Operations

Semantic Data Engineer | Digital Operations

BETA Technologies

South Burlington, VT

$114K - $138K/yr

Other

Posted 18 days ago

Job description

We are seeking a Semantic Data Engineer to join our Data and AI Platform team, bringing deep expertise in semantic technologies, linked data, and metadata management to help design and build intelligent data platforms that unlock the full value of our organization's information assets. In this role, you will combine strong data engineering fundamentals with specialized knowledge of semantic modeling and data interoperability to create robust, scalable solutions that enable rich data discovery, automated reasoning, and seamless integration across diverse data sources. You will work collaboratively with data scientists, platform engineers, and domain experts to evaluate, architect, and implement the most appropriate semantic solutions while ensuring they integrate seamlessly with our broader data and AI infrastructure. The ideal candidate is a pragmatic technologist who can translate complex business requirements into elegant semantic data models and has hands-on experience building production-ready systems that make data more findable, accessible, and reusable across the enterprise.
 
How you will contribute to revolutionizing electric aviation:
  • Design and build scalable data platform capabilities that empower domain teams through extensible frameworks and standards, enabling them to manage their data assets within a cohesive semantic architecture spanning the enterprise
  • Implement robust data integration solutions and unified namespace patterns that create a digital thread connecting real-time and historical information across the entire product lifecycle-from design through manufacturing to field operations
  • Build optimized data storage architectures and metadata management systems including data lakes, warehouses, knowledge graphs, and enterprise catalogs that make all organizational knowledge discoverable and actionable
  • Develop semantic layers and ontologies that capture domain expertise and business logic, making implicit organizational knowledge explicit and machine-readable in formats that both humans and AI systems can leverage, while preserving traceability across the product lifecycle
  • Create unified data access services that expose the digital thread to stakeholders across the organization, breaking down silos between engineering, manufacturing, operations, and business teams
  • Implement data quality frameworks and lineage solutions that ensure accuracy across diverse data types while illuminating information flow through complex systems-essential for aerospace compliance, continuous improvement, and establishing the trusted data foundation required for advanced analytics and AI
  • Partner with cross-functional teams to strengthen the digital thread through DataOps practices and champion data governance standards that keep our diverse data assets trusted, accessible, and valuable
  • Actively contribute to a collaborative team environment through code reviews, knowledge sharing, and constructive feedback that continuously improves our data solutions and maintains high engineering standards
Minimum Qualifications:
  • Bachelor's degree in Computer Science, Information Systems, Data Science, or related technical field (or equivalent practical experience)
  • 3+ years of professional experience in data engineering or related field
  • Hands-on experience with semantic technologies, knowledge graphs, or linked data systems
  • Experience designing and implementing ontologies, taxonomies, or semantic data models
  • Proficiency with modern data engineering tools and languages (e.g., Python, SQL)
  • Experience with graph databases (e.g., Neo4j, Amazon Neptune, Stardog) and/or triple stores
  • Strong understanding of data integration patterns and API design
  • Excellent communication skills with ability to translate technical concepts for diverse audiences
  • Experience with cloud platforms (preferably AWS)
  • Experience with DataOps practices and modern data platform architectures (cloud and hybrid)
  • Understanding of DevOps practices including CI/CD, version control (Git), and infrastructure as code
  • Ability to work collaboratively in a fast-paced environment
  • Exceptional troubleshooting skills with the ability to spot issues before they become problems
Above and Beyond Qualifications:
  • Advanced degree in Computer Science or related field
  • 5+ years of experience specifically working with semantic technologies in production environments
  • Expert-level knowledge of semantic web standards (RDF, OWL, SPARQL, SHACL)
  • Experience building and scaling knowledge graphs in enterprise settings
  • Proficiency with additional programming languages (e.g., Scala, Java) and distributed computing frameworks (Spark, Flink)
  • Hands-on experience with metadata management platforms and enterprise data catalogs
  • Track record of implementing data lineage and data quality solutions at scale
  • Experience working in regulated industries or with complex data governance frameworks
  • Familiarity with aerospace/manufacturing data standards
  • Knowledge of IoT protocols and time-series data management
  • Publications, presentations, or open-source contributions in semantic technologies
  • Familiarity with aviation regulations and standards (DO-178, DO-254, DO-330 etc.) as they relate to data systems

Apply