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Metadata Manager Jobs in Pennsylvania (NOW HIRING)

PineQ Lab Technology

Lead Data Modeler

Malvern, PA · On-site

$53.75 - $69.75/hr

Demonstrated expertise in conceptual, logical, canonical, semantic, and physical data modeling. • Deep understanding of enterprise information architecture and metadata management. • Experience ...

System One

Data Engineer - Databricks

Pittsburgh, PA · On-site

$111K - $133K/yr

Implement and manage Unity Catalog to support enterprise data governance, security, metadata management, and fine-grained access control. . Develop cloud native data engineering solutions on the ...

QVC

Media Asset Manager

West Chester, PA · Hybrid

You will manage the end-to-end lifecycle of our media assets, including ingest, metadata application, quality control, storage, distribution, archiving, and retention. * You will oversee enterprise ...

Cleon Incorporated

Information/Data Architect

Reading, PA · On-site

$61.25 - $78.75/hr

Metadata management * Data quality * Business intelligence/data warehousing * Data interoperability * Analytics * Data integration and aggregation The Information Architect should be able to assist ...

Cleon Incorporated

Information/Data Architect

Reading, PA · On-site

$61.25 - $78.75/hr

Metadata management * Data quality * Business intelligence/data warehousing * Data interoperability * Analytics * Data integration and aggregation The Information Architect should be able to assist ...

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All JobsMetadata JobsMetadata Manager JobsMetadata Manager Jobs in Pennsylvania

Metadata Manager information

See Pennsylvania salary details

$27.6K

$81.9K

$137.8K

How much do metadata manager jobs pay per year?

As of Sep 4, 2026, the average yearly pay for metadata manager in Pennsylvania is $81,873.00, according to ZipRecruiter salary data. Most workers in this role earn between $50,100.00 and $116,800.00 per year, depending on experience, location, and employer.

What is a metadata manager?

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.

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 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.

What are the most commonly searched types of Metadata jobs in Pennsylvania?

The most popular types of Metadata jobs in Pennsylvania are:

What are popular job titles related to Metadata Manager jobs in Pennsylvania?

For Metadata Manager jobs in Pennsylvania, the most frequently searched job titles are:

What job categories do people searching Metadata Manager jobs in Pennsylvania look for?

The top searched job categories for Metadata Manager jobs in Pennsylvania are:

Metadata Manager jobs near you
Infographic showing various Metadata Manager job openings in Pennsylvania as of August 2026, with employment types broken down into 82% Full Time, 17% Part Time, and 1% Contract. Highlights an 81% Physical, 2% Hybrid, and 17% Remote job distribution, with an average salary of $81,873 per year, or $39.4 per hour.

Lead Data Modeler

PineQ Lab Technology

Malvern, PA • On-site

$53.75 - $69.75/hr

Other

This job post has expired 1 day ago. Applications are no longer accepted.

Job description

Demonstrated expertise in conceptual, logical, canonical, semantic, and physical data modeling.

• Deep understanding of enterprise information architecture and metadata management.

• Experience developing business-oriented canonical models independent of application implementations.

• Strong understanding of business rule modeling, cardinality, optionality, integrity constraints, and

relationship semantics.

• Expertise in enterprise modeling patterns such as Party, Role, Agreement, and Classification.

• Strong understanding of Supertype / subtype modeling, Temporal modeling. Associative entities, Reference

data design, and Master data concepts

• Experience supporting analytics, regulatory reporting, operational data quality, and AI-enabled business use

cases through enterprise data modeling.

• Experience establishing or contributing to enterprise data modeling, governance and stewardship functions.

• Experience with enterprise data modeling tools such as ERwin, ER Studio, and maintaining enterprise data

dictionaries.

• Ability to create reusable business concepts and canonical models that support long-term information

architecture strategy.

Roles & Responsibilities

• Partner with business data stewards and product teams to define and evolve business concepts, entities, relationships, and business rules. • Own the holistic Personal Wealth logical and canonical data model and maintain traceability to implementation assets. • Lead development of canonical models supporting householding, advisor teaming, client relationships, investment offerings, and operational workflows. • Support strategic initiatives such as Portfolio of the Future by designing canonical models and abstraction layers that isolate Vanguard business concepts from vendor-specific schemas. • Define standards and best practices for conceptual, logical, physical, canonical, and semantic data modeling. • Establish governance processes supporting model stewardship, versioning, lifecycle management, and change control. • Partner with Enterprise Data Architecture and Engineering teams to implement tooling supporting model management, metadata management, lineage, and governance. • Collaborate with integration teams to design Anti-Corruption Layer (ACL) patterns and mapping frameworks between vendor platforms and Vanguard canonical data models. • Facilitate workshops to identify, define, and validate enterprise business concepts and relationships. • Mentor architects, analysts, and engineers in modern data modeling practices. • Support data models used across advice delivery, wealth management, client servicing, analytics, regulatory reporting, and AI-enabled experiences. • Drive adoption of enterprise modeling standards and reusable business concepts across product and engineering teams. • Establish and promote common business language and shared enterprise concepts across Personal Wealth platforms. • Ensure canonical models provide a stable abstraction layer between business domains, internal systems, and vendor platforms.


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