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Metadata Assistant Jobs in Wisconsin (NOW HIRING)

Senior AI Data Engineer

Wauwatosa, WI · On-site

$121K - $151K/yr

... understanding, metadata intelligence, AI-ready data abstractions, and agent-driven platform ... assistants or prototypes. * Experience with AI frameworks and platforms such as Google ADK, Vertex ...

... understanding, metadata intelligence, AI-ready data abstractions, and agent-driven platform ... assistants or prototypes. * Experience with AI frameworks and platforms such as Google ADK, Vertex ...

Data Architect (954)

Beloit, WI · On-site

$62.25 - $80.25/hr

... then assist in the design, documentation, and care of solutions. Working in a collaborative ... Metadata, Taxonomy, and Lineage Architecture * AI-Ready Data Foundations You will serve as the ...

Data Architect (954)

Beloit, WI · On-site

$130 - $180/hr

... then assist in the design, documentation, and care of solutions. Working in a collaborative ... Enable secure self-service access to trusted enterprise data through governance, metadata, semantic ...

Configure, maintain, and optimize Oracle EPBCS applications, metadata, business rules, security ... Monitor forecast accuracy and assist in identifying key business drivers and variances. * Perform ...

... Erwin Assist Data Administration Services in transitioning enterprise logical data model structure into application specific database schemas Manage and administer metadata repository Work with ...

Apply basic regulatory requirements (FDA, USDA, TTB) to documentation checks * Assist with annual ... Enter and validate metadata in documentation systems * Help troubleshoot simple file issues ...

Apply basic regulatory requirements (FDA, USDA, TTB) to documentation checks * Assist with annual ... Enter and validate metadata in documentation systems * Help troubleshoot simple file issues ...

Finance Systems Analyst I

Waukesha, WI · On-site

$86K - $116K/yr

Maintain metadata, workflows, dashboards, and reports with direction from Finance Systems Manager ... Work with Finance, Accounting, and FP&A users to understand reporting needs and assist in ...

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Metadata Assistant information

What is a metadata assistant?

Metadata Assistants are professionals who support the organization, management, and maintenance of metadata in libraries, archives, museums, or digital collections. Their primary role involves creating, editing, and ensuring the accuracy of metadata records, which helps users locate and access resources efficiently. They may also assist with data entry, quality control, and the application of cataloging standards. Metadata Assistants work closely with librarians, archivists, and other information professionals to maintain high-quality information systems.

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

To thrive as a Metadata Assistant, you need a detail-oriented mindset, familiarity with metadata standards, and a background in library science or information management. Experience with cataloging systems, library management software, and knowledge of standards such as MARC or Dublin Core is commonly required. Strong organizational skills, accuracy, and effective communication help you excel in updating and maintaining metadata records. These skills ensure the accurate organization, retrieval, and accessibility of digital and physical information resources.

What are some common challenges faced by metadata assistants, and how can they be addressed?

Metadata Assistants often encounter challenges such as ensuring data accuracy, maintaining consistency across different cataloging standards, and managing large volumes of information. Staying up-to-date with changing metadata standards and mastering various database systems can also be demanding. To address these challenges, it’s helpful to participate in ongoing professional development, collaborate closely with catalogers and IT staff, and utilize quality control tools to regularly audit and correct metadata entries. Building strong communication skills and being detail-oriented are key assets in this role.

What is the difference between Metadata Assistant vs Data Entry Clerk?

AspectMetadata AssistantData Entry Clerk
Required SkillsKnowledge of metadata standards, attention to detail, basic database skillsTyping accuracy, data input, basic computer skills
Work EnvironmentLibraries, archives, digital repositoriesOffices, administrative settings
CertificationsOften none, but familiarity with cataloging standards helpsNone typically required
Industry UsageLibraries, museums, digital asset managementVarious industries, administrative roles

The main difference is that Metadata Assistants focus on organizing and maintaining digital or physical metadata to improve asset retrieval, while Data Entry Clerks primarily input and manage data accuracy in databases. Metadata Assistants require knowledge of metadata standards and work in specialized environments, whereas Data Entry Clerks perform general data input tasks across various industries.

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

The most popular types of Metadata jobs in Wisconsin are:

What are popular job titles related to Metadata Assistant jobs in Wisconsin?

For Metadata Assistant jobs in Wisconsin, the most frequently searched job titles are:

What job categories do people searching Metadata Assistant jobs in Wisconsin look for?

The top searched job categories for Metadata Assistant jobs in Wisconsin are:

Infographic showing various Metadata Assistant job openings in Wisconsin as of August 2026, with employment types broken down into 2% As Needed, 77% Full Time, 18% Part Time, 1% Temporary, and 2% Contract. Highlights an 98% Physical, 1% Hybrid, and 1% Remote job distribution.

Senior AI Data Engineer

Wauwatosa, WI • On-site

$121K - $151K/yr

Full-time

Re-posted 4 days ago


Job description

We are seeking a highly experienced Senior AI Data Engineer to help transform our Enterprise Data Platform into an AI-native, intelligent platform where AI agents can discover, understand, and interact with enterprise data and platform capabilities.
This role focuses on building the foundations that enable AI agents and intelligent applications to effectively leverage enterprise data, including context engineering, semantic understanding, metadata intelligence, AI-ready data abstractions, and agent-driven platform capabilities.
This is a hands-on senior role requiring deep expertise in cloud data engineering, AI-enabled data platforms, agentic AI architectures, semantic modeling, metadata and context engineering, and modern software development practices. The ideal candidate combines strong technical execution skills with architectural thinking and the ability to design and deliver scalable AI capabilities that integrate seamlessly with enterprise data platforms and business workflows.We offer:
  • Career Development
  • Competitive Compensation and Benefits
  • Pay Transparency
  • Global Opportunities

Learn More Here:https://www.dematic.com/en-us/about/careers/what-we-offer

Dematic provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.

The base pay range for this role is estimated to be $121,200.00 - $151,500.00 at the time of posting. Final compensation will be determined by various factors such as work location, education, experience, knowledge and skills.

Tasks and Qualifications:

This is What You Will do in This Role:

  • Evolve the Enterprise Data Platform into an AI-native platform by enabling intelligent discovery, understanding, and utilization of enterprise data.
  • Design and implement AI-driven capabilities and agents that enhance data platform capabilities, automate complex workflows, and improve how data is discovered, managed, governed, and consumed.
  • Build the data intelligence foundation required for AI systems, including trusted context, business understanding, and reliable access to enterprise data.
  • Design architectures that enable AI systems to reason over enterprise data and safely interact with platform capabilities, APIs, services, and enterprise applications.
  • Develop scalable AI-enabled solutions that integrate with cloud data platforms, distributed systems, and modern software architectures.
  • Establish engineering practices for reliable production AI capabilities, including security, governance, evaluation, monitoring, and operational excellence.
  • Apply strong data engineering and software engineering principles to build scalable, maintainable AI-enabled platform capabilities.
  • Partner with data, AI/ML, architecture, and product teams to identify and deliver high-impact AI capabilities for the enterprise data platform.
  • Mentor engineers and define best practices for AI-enabled data platform development.

What We are Looking For:

  • 8-12+ years of experience in enterprise software engineering, cloud data engineering, distributed systems, or data platform development.
  • Hands-on experience designing and building production AI systems, AI agents, or agentic workflows integrated with enterprise applications, APIs, and platform services.
  • Strong understanding of AI agent architectures, including tool calling, orchestration, context management, memory, evaluation, observability, and production deployment patterns.
  • Experience building AI-ready data platforms with capabilities such as semantic understanding, metadata intelligence, context engineering, and trusted data access.
  • Strong cloud data engineering experience, preferably in GCP, including BigQuery, Pub/Sub, Dataflow/Cloud Run, Composer/Airflow, and modern data platform services.
  • Strong programming skills in Python and experience building scalable software services, APIs, and microservice architectures.
  • Deep understanding of data engineering fundamentals, including data modeling, data contracts, metadata, lineage, governance, data quality, and batch/streaming architectures.
  • Experience integrating AI capabilities with enterprise data platforms and distributed systems.
  • Experience with modern data and cloud-native technologies such as Iceberg, Trino, Kubernetes, and Docker.
  • Experience designing secure, governed, and observable production AI solutions, including evaluation, monitoring, and operational excellence.

What Will Set You Apart:

  • Experience building AI agents that execute real-world enterprise workflows, beyond conversational assistants or prototypes.
  • Experience with AI frameworks and platforms such as Google ADK, Vertex AI, MCP, LangGraph, or similar technologies.
  • Experience applying RAG, embeddings, vector search, semantic layers, or knowledge graphs to enterprise AI solutions.
  • Experience with Data Mesh, domain-driven data architecture, or federated data platforms.
  • Supply chain, logistics, warehouse automation, or industrial domain experience.

Location & Authorization:This is a hybrid role requiring proximity to one of our U.S. offices (Atlanta GA, Grand Rapids MI, Milwaukee WI).Applicants must be authorized to work in the U.S. without the need for current or future sponsorship.

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