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Entry Level Metadata Analyst Jobs (NOW HIRING)

The Associate Data Analyst/Metadata Analyst manages the lifecycle of bibliographic and holdings ... This entry-level role combines metadata expertise with developing technical skills in scripting ...

... entry-level Data Analyst to support enterprise asset data management initiatives. This role will ... Exposure to data governance, data quality, or metadata management concepts. * Experience working ...

JOB LEVEL/FLSA STATUS: Entry Level FUNCTION: Product Content SUBFUNCTION: Digital Assets REPORTS TO ... asset metadata as necessary * Partner with Product Management, Engineering & Brand Marketing for ...

JOB LEVEL/FLSA STATUS: Entry Level FUNCTION: Product Content SUBFUNCTION: Digital Assets REPORTS TO ... asset metadata as necessary * Partner with Product Management, Engineering & Brand Marketing for ...

Data Analyst

$60K - $70K/yr

Salary Range: $60,000 - $70,000 Annually ABOUT THE ROLE As an entry-level Data Analyst, you will ... metadata, under the guidance of senior analysts. - Support efforts to keep data accurate and ...

Data Engineer I

Gainesville, FL · On-site

$65K - $78K/yr

... metadata management. This entry-level role, under direct supervision, entails close collaboration with customers, business analysts, and team members. Your primary focus is to understand business ...

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Entry Level Metadata Analyst information

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How much do entry level metadata analyst jobs pay per hour?

As of Aug 26, 2026, the average hourly pay for entry level metadata analyst in the United States is $38.63, according to ZipRecruiter salary data. Most workers in this role earn between $25.96 and $48.32 per hour, depending on experience, location, and employer.

What does an entry level metadata analyst do?

An Entry Level Metadata Analyst is responsible for organizing, categorizing, and maintaining data about data—known as metadata—within an organization. Their job involves ensuring the accuracy, completeness, and consistency of metadata to help other users easily find and use information. They may also assist in developing metadata standards, performing quality checks, and supporting data governance initiatives. This role is critical for enhancing data accessibility and supporting business intelligence efforts.

What are the key skills and qualifications needed to thrive as an entry level metadata analyst, and why are they important?

To thrive as an Entry Level Metadata Analyst, you need a solid understanding of data management principles, attention to detail, and a bachelor's degree in information science, library science, or a related field. Familiarity with metadata standards (such as Dublin Core), data cataloging tools, and database systems is typically required. Strong analytical thinking, problem-solving, and effective communication skills help you excel in managing and organizing data assets. These skills ensure accurate metadata creation, efficient data retrieval, and support organizational data governance efforts.

What are some common challenges faced by entry level metadata analysts and how can they be overcome?

Entry level metadata analysts often face challenges such as learning complex data management systems, ensuring metadata accuracy, and understanding organizational data standards. To overcome these, it's helpful to actively seek mentorship from experienced team members, participate in training sessions, and regularly consult documentation and guidelines. Collaborating closely with data engineers and librarians can also clarify expectations and promote consistency, helping new analysts build confidence and accuracy in their work.

What is the difference between Entry Level Metadata Analyst vs Data Coordinator?

AspectEntry Level Metadata AnalystData Coordinator
Required CredentialsBachelor's in Information Science, Library Science, or related fieldBachelor's in Data Management, Information Systems, or related field
Work EnvironmentData management teams, IT departments, librariesData management teams, administrative offices, data centers
Employer & Industry UsageMedia, libraries, tech companies, research institutionsHealthcare, government agencies, corporate data teams
Common Search & ComparisonYesYes

The Entry Level Metadata Analyst and Data Coordinator roles share similarities in required education and work environments, often found in data-driven industries. While both handle data management tasks, Metadata Analysts focus more on organizing and maintaining metadata for digital assets, whereas Data Coordinators oversee broader data collection, validation, and reporting processes. Understanding these distinctions helps job seekers identify the best fit for their skills and career goals.

More about Entry Level Metadata Analyst jobs

What are the most commonly searched types of Metadata Analyst jobs?

The most popular types of Metadata Analyst jobs are:

What states have the most Entry Level Metadata Analyst jobs?

States with the most job openings for Entry Level Metadata Analyst jobs include:

What job categories do people searching Entry Level Metadata Analyst jobs look for?

The top searched job categories for Entry Level Metadata Analyst jobs are:

Infographic showing various Entry Level Metadata Analyst job openings in the United States as of August 2026, with employment types broken down into 90% Full Time, 5% Part Time, and 5% Contract. Highlights an 80% Physical, 8% Hybrid, and 12% Remote job distribution, with an average salary of $80,350 per year, or $38.6 per hour.

Associate Data/ Metadata Analyst

Dublin, OH • Hybrid

Full-time

Medical, Retirement

Posted 15 days ago


Job description

Together we make breakthroughs possible.

At OCLC, we build technology with a purpose: to connect libraries and make knowledge accessible worldwide, because we believe that what is known must be shared. Our teams work with complex global datasets, AI and machine learning, hybrid cloud solutions, and other technologies that connect people and organizations to the information they need. We value the power of unique perspectives and experiences to unlock innovation. At OCLC, your ideas matter, whether you have two years of experience or 20. You'll learn, create, and problem-solve with technologists, product developers, librarians, researchers, marketing pros, and support teams around the world.

Why join OCLC?

OCLC is consistently recognized as a best place to work by several independent programs. Werecognize and reward people and results with a comprehensive Total Rewards package. This means competitive compensation that reflects your unique contributions-performance, experience, and skills-along with exceptional benefits, including best-in-class health coverage, retirement plans with generous company contributions, and a commitment to your overall well-being.

  • We know the best ideas don't always happen at a desk. Take a walking meeting around our 100-acre campus or enjoy lunch on the patio. We're committed to your success-both personally and professionally. Hybrid work environment: For many roles, three days a week on-site, with occasional additional days based on business needs.

  • Free use of our on-site tness center, gym sports, group exercise classes, and game room

  • Onsite catering and cafeteria subsidized by OCLC

  • Health and wellness events

  • Work environments with individual and team spaces and the latest technology tools

  • Paid parental leave and adoption assistance

  • Tuition reimbursement and Public Service Loan Forgiveness eligibility

  • Company-subsidized pricing on local tickets and memberships

Join us in transforming how people everywhere access information and be part of a mission-driven team that makes a global impact.

The job details are as follows:The Associate Data Analyst/Metadata Analyst manages the lifecycle of bibliographic and holdings data, ensuring accuracy and integrity through evaluation, transformation, and maintenance. This entry-level role combines metadata expertise with developing technical skills in scripting, automation, and AI-assisted workflows. Working under regular supervision, the Associate will transition from executing well-defined tasks to taking ownership of complex data projects. This is an opportunity to develop expertise at the intersection of library data, modern data engineering, and emerging AI - in a team that invests in the growth of its people.Responsibilities:Data Operations & Quality
  • Data Lifecycle Management:Perform data ingest, normalization, enrichment, and matching according to established standards (e.g., MARC, KBART).
  • Quality Assessment:Profile incoming data to identify and resolve structural issues, encoding errors, and tagging discrepancies.
  • Troubleshooting:Investigate and resolve data quality issues, escalating complex problems to senior staff as needed.
  • Vendor Communication:Coordinate with external data providers and partner institutions regarding routine data specifications and quality issues.
Technical Solutions & Automation
  • Pipeline Support:Apply existing scripts and automated workflows to process data; identify inefficiencies and suggest process improvements.
  • Data Visualization:Use and interpret dashboards (e.g., Power BI) to monitor data quality trends and communicate findings.
  • AI Integration:Utilize AI-assisted tools for record matching and field mapping; contribute structured feedback that helps improve AI model accuracy over time.
Collaboration & Documentation
  • Knowledge Management:Document data source profiles, processing decisions, and technical workflows to ensure team-wide knowledge sharing.
  • Team Support:Execute foundational tasks to support senior analysts and participate in platform improvement projects.
Minimum Required Knowledge, Skills and Experience:
  • Bachelor's degree in computer science, math, statistics, or related field and internship experience with data analysis or creation of library data.
  • Entry-level analytical and communication skills, with attention to data quality while working under regular supervision.
Preferred Knowledge, Skills and Experience:
  • Metadata Standards:Foundational knowledge of MARC, Dublin Core, KBART, or BIBFRAME.
  • Technical Tools:Exposure to scripting languages (Python, SQL, or XSLT) and data transfer protocols (SFTP, APIs, or AWS S3).
  • Data Platforms:Conceptual familiarity with cloud data stores (e.g., Snowflake) and visualization tools (e.g., Power BI, Streamlit).
  • Emerging Tech:Interest in applying AI and linked data concepts (e.g.,Schema.org) to library data challenges.
Working Conditions: Normal office environment.ADA/EAA: The above statements cover what are generally believed to be principal and essential functions of this job. Specific circumstances may allow or require some people assigned to the job to perform a somewhat different combination of duties.