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Metadata Curator Jobs in Michigan (NOW HIRING)

Tech Tammina LLC

Data / BI Architect

Pontiac, MI · On-site

Design, create & maintain an enterprise-wide data catalog, automating metadata ingestion ... curating & organizing data assets in an intuitive way. • Performance Optimization: Monitor ...

Torc Robotics

Senior, ML Engineer - Auto Tagger

Ann Arbor, MI · On-site +1

$102K - $140K/yr

... metadata integrity. * Data Flywheel Integration: Manage the ingestion of tagged events into the ... ML & Dataset Curation: Hands-on machine learning and dataset curation experience, with a ...

Converys

Data Architect

East Lansing, MI

$96K - $130K/yr

Define standards for data modeling, data quality, naming conventions, metadata, lineage, and ... Design and oversee medallion-style data layers (bronze/silver/gold) for ingestion, curation, and ...

Ford Motor Company

Analytics Scientist

Dearborn, MI · On-site +1

$140K - $182K/yr

... curation including Informatica and Cognos skills. 6. Designing and implementing large-scale logical, physical, or metadata data models. 3 years of experience with each of the following skills is ...

Ford Motor Company

Analytics Scientist

Dearborn, MI · On-site

$140K - $182K/yr

... curation including Informatica and Cognos skills. 6. Designing and implementing large-scale logical, physical, or metadata data models. 3 years of experience with each of the following skills is ...

All JobsMetadata Curator JobsMetadata Curator Jobs in Michigan

Metadata Curator information

See Michigan salary details

$22.2K

$63.3K

$104.2K

How much do metadata curator jobs pay per year?

As of Jul 26, 2026, the average yearly pay for metadata curator in Michigan is $63,301.00, according to ZipRecruiter salary data. Most workers in this role earn between $43,600.00 and $81,900.00 per year, depending on experience, location, and employer.

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

To thrive as a Metadata Curator, you need expertise in information science, data management, and taxonomy development, often supported by a degree in library science or a related field. Familiarity with metadata standards (like Dublin Core or MARC), cataloging software, and data repository systems is typically required. Attention to detail, analytical thinking, and strong organizational and communication skills help ensure accurate and consistent metadata creation. These skills are crucial for making data easily discoverable, interoperable, and usable across digital platforms.

What are some common challenges Metadata Curators face when standardizing data from multiple sources?

Metadata Curators often encounter the challenge of integrating and standardizing data from diverse sources, which may use varying formats, terminologies, or metadata schemas. Ensuring consistency, accuracy, and completeness across these datasets requires close attention to detail and a solid understanding of metadata standards. Collaborating with data providers and technical teams is crucial to resolve discrepancies and establish clear guidelines for metadata management. Adapting to evolving data standards and maintaining documentation are also key aspects of the role.

What are Metadata Curators?

Metadata Curators are professionals responsible for organizing, managing, and maintaining metadata, which is data that describes other data. They ensure that information about digital assets—such as documents, images, or datasets—is accurate, consistent, and easily searchable. Their work helps improve data discoverability, interoperability, and long-term access in libraries, archives, museums, and digital repositories. Metadata Curators often collaborate with data creators and users to establish and apply metadata standards. Their expertise is essential for effective data management and information retrieval.

What is the difference between Metadata Curator vs Data Analyst?

AspectMetadata CuratorData Analyst
Required CredentialsBachelor's in Library Science, Information Management, or related fields; familiarity with metadata standardsBachelor's in Statistics, Data Science, or related fields; proficiency in data analysis tools
Work EnvironmentLibraries, archives, museums, digital repositoriesBusiness, finance, healthcare, tech companies
Employer & Industry UsageOrganizations managing digital assets and information resourcesOrganizations analyzing data to inform decisions
Common Search & Comparison IntentUnderstanding roles related to managing metadata and digital contentUnderstanding roles focused on analyzing and interpreting data

While both roles involve working with data, a Metadata Curator primarily manages and organizes metadata for digital assets, ensuring accurate description and discoverability. A Data Analyst interprets data sets to provide insights and support decision-making. The roles often overlap in data management but differ in focus and industry application.

What are popular job titles related to Metadata Curator jobs in Michigan? For Metadata Curator jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Metadata Curator jobs in Michigan look for? The top searched job categories for Metadata Curator jobs in Michigan are:
Metadata Curator jobs near you
Infographic showing various Metadata Curator job openings in Michigan as of July 2026, with employment types broken down into 67% Full Time, 31% Part Time, 1% Temporary, and 1% Contract. Highlights an 98% Physical, 1% Hybrid, and 1% Remote job distribution, with an average salary of $63,301 per year, or $30.4 per hour.
Data / BI Architect

Data / BI Architect

Tech Tammina LLC

Pontiac, MI • On-site

Contractor

Posted 22 days ago

Job description

Role: Data / BI Architect

Location: Pontiac, MI

Duration: 12Months +

About role:

Data Business Intelligence (BI) Architect role is a hybrid of data architecture, engineering & business strategy, bridging the gap between tech data solutions & business objectives. Designs, develops & maintains the overall data strategy ensuring the County data in scope is accessible, reliable & secure for analysis and decision-making. The right candidate has experience in architecting data solutions that can be used for descriptive, diagnostic, predictive & prescriptive analytic solutions.

KEY RESPONSIBILITIES:

•       Stakeholder Collaboration: Work closely with business & IT stakeholders to gather req & translate business needs into tech specifications, including identification of data sources.

•       Data Arch Design & Data Modeling: Architect & implement scalable, secure & efficient data solutions, including data warehouses, data lakes, and/or data marts.

•       Design conceptual, logical & physical data models.

•       Tool and Platform Selection: Evaluate, recommend & implement tools aligned with recommended architecture, including visualization tools aligned with business needs.

•       ETL/ELT Pipeline Mgt: Design, develop & test data pipelines, integrations to source mgt & ETL / ELT processes to move data from various sources into the data warehouse.

•       Data Catalog & Metadata Mgt: Design, create & maintain an enterprise-wide data catalog, automating metadata ingestion, establishing data dictionaries, and ensuring that all data assets are properly documented & tagged.

•       Data Governance and Discovery: Enforce data governance policies through the data catalog, ensuring data quality, security & compliance.

•       Enable self-service data discovery for users by curating & organizing data assets in an intuitive way.

•       Performance Optimization: Monitor & optimize BI systems & data pipelines to ensure high performance, reliability & cost-effectiveness.

•       Technical Leadership: Provide technical guidance & mentorship across the organization, establishing best practices for data mgt & BI development.

Environment:

•       Role incl. defining data platform tech stack. Example tech below; not required to have experience in all.

•       Data Platforms: DW & lake concepts incl. dimensional modeling & cloud services (S3, AWS Redshift, RDS, Azure Data Lake Storage, Synapse Analytics, BigQuery, Databricks, Snowflake, Informatica);

•       Databases: SQL & relational/non-relational (SQL Server, Oracle, PostgreSQL, MongoDB);

•       BI Tools: Power BI, Business Objects, Tableau, Crystal, Looker;

•       ETL/ELT: Cloud native (AWS Glue, Azure Data Factory, Google Cloud Dataflow) & in-warehouse transform tools (Fivetran, Talend, dbt);

•       Big Data Tech: Hadoop, Spark, Kafka;

•       Programming/API: Python, Keras, Scikit-learn, R, XML;

•       ML/DL/Analytic Engines: TensorFlow, PyTorch, Trillium, Apache Spark;

•       Modeling Tools: MS Visio, ER/Studio, PowerDesigner;

•       Source systems incl. on-prem, cloud, & SaaS;