ZipRecruiter

Log In

1

Metadata Library Jobs in Everett, WA (NOW HIRING)

Hirekeyz Inc

Solution Architect

Redmond, WA · On-site

$70.50 - $93/hr

Configure contract templates, workflows, clauses, metadata fields, and approval rules. * Maintain ICM rulesets, permission sets, contract types, clause libraries, and smart rules. * Define and ...

Apex Systems

Salesforce Devleoper

Bellevue, WA

$50 - $60/hr

Familiarity with data migration tools (Data Loader, APIs, ETL tools), metadata deployments, and org ... library of technical and leadership courses/books/seminars once you have 6+ months of tenure, and ...

Epitec

Knowledge Intelligence Partner III

Seattle, WA · On-site

$107K - $134.90K/yr

Tag and categorize content using established taxonomies and metadata standards * Generate usage ... Bachelor's degree in information management, library science, communications, or related field Must ...

Uw

Research Scientist/Engr 1

Seattle, WA

$58.01K/yr

... metadata, and maintain clean experimental records that support downstream analysis and sponsor ... Sequencing library preparation or sample-prep familiarity for assay readouts. Experience with ...

next page

Showing results 1-20

People also search for

All JobsMetadata Library JobsMetadata Library Jobs in Everett, WA

Metadata Library information

See Everett, WA salary details

$9

$20

$30

How much do metadata library jobs pay per hour?

As of May 31, 2026, the average hourly pay for metadata library in Everett, WA is $20.64, according to ZipRecruiter salary data. Most workers in this role earn between $16.73 and $23.37 per hour, depending on experience, location, and employer.

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

To thrive as a Metadata Librarian, you need expertise in cataloging standards (such as MARC, Dublin Core), metadata schema, and information organization, usually supported by a Master's in Library Science or a related field. Familiarity with integrated library systems (ILS), metadata management tools, and knowledge of cataloging software like OCLC Connexion is typical. Attention to detail, analytical thinking, and strong communication skills help ensure accuracy and facilitate collaboration with library staff. These skills and qualities are crucial to maintaining accessible, well-organized digital and print collections that support user discovery and research.

What are some common challenges faced by professionals working in a metadata library role, and how can they be addressed?

Professionals in a metadata library role often encounter challenges such as maintaining consistency and accuracy in metadata standards across diverse collections, keeping up with evolving cataloging guidelines, and integrating new technologies or platforms. Addressing these challenges typically involves ongoing training, collaboration with colleagues to develop clear metadata policies, and staying informed about industry best practices. Regular communication with IT teams and subject specialists is also key to ensuring that metadata effectively supports discoverability and access for library users.

What are metadata librarians and what do they do?

Metadata librarians are information professionals who manage and organize metadata, which is data that describes other data, for library collections. They create, edit, and maintain metadata records to ensure resources are discoverable, accessible, and properly described in library catalogs and digital repositories. Their work supports searchability, digital preservation, and resource sharing by applying standards and best practices for cataloging. Metadata librarians often collaborate with IT staff, archivists, and subject specialists to enhance user access to library materials.

Can you make 6 figures as a librarian?

While most librarians earn below six figures, some specialized roles such as library directors or those working in large institutions with advanced degrees and certifications can reach or exceed a six-figure salary. Achieving this level often requires extensive experience, additional qualifications, and leadership responsibilities.

What is the difference between Metadata Library vs Metadata Specialist?

AspectMetadata LibraryMetadata Specialist
CredentialsTypically requires a degree in library science, information management, or related fieldsRequires similar credentials, often with additional certifications in data management or information systems
Work EnvironmentLibraries, archives, or information centers managing large metadata collectionsData-driven organizations, digital repositories, or information management teams
Employer & IndustryLibraries, museums, archives, academic institutionsTech companies, publishing, digital content providers
Search & Comparison IntentUnderstanding library metadata management rolesSpecialized data and metadata management tasks

The main difference is that a Metadata Library focuses on managing metadata within library and archival settings, while a Metadata Specialist handles metadata in broader digital and data environments. Both roles require similar credentials but serve different industry needs.

What are popular job titles related to Metadata Library jobs in Everett, WA? For Metadata Library jobs in Everett, WA, the most frequently searched job titles are:
What job categories do people searching Metadata Library jobs in Everett, WA look for? The top searched job categories for Metadata Library jobs in Everett, WA are:
What cities near Everett, WA are hiring for Metadata Library jobs? Cities near Everett, WA with the most Metadata Library job openings:
Metadata Library jobs near you
AI Architect -- Agentic Data Modernisation (IDM Platform)

AI Architect -- Agentic Data Modernisation (IDM Platform)

Rivi Consulting Group

Seattle, WA

$72.50 - $93.25/hr

Other

Posted 11 days ago

Job description

AI Architect — Agentic Data Modernization (IDM Platform)

Roles & Responsibilities

• Design multi-agent orchestration frameworks using Lang Graph — stateful graphs, conditional routing, agent handoff, retry and fallback logic

• Build agent harnesses coordinating Discovery, Parsing, Mapping, Code Generation, Validation, and Review agents across a shared execution context

• Develop the IDM prompt library prompts, few-shot templates, structured output schemas, and reflection loops for each conversion workstream

• Build LLM-powered code conversion pipelines ex: DataStage → Databricks PySpark, Dremio SQL → Snowflake SQL, legacy ETL → cloud-native equivalents

• Lead AICH–IDM platform integration — capability merger, MCP server design, shared tool registry, unified agentic execution surface

• Architect and operate conversion pipelines for 50,000–80,000+ legacy objects with parallelism, batching, resumability, and audit logging

• Build metadata frameworks for conversion traceability — extraction run tracking, job dependency graphs, column-level lineage, confidence scoring

• Implement LLM routing layers that select models (Claude, OpenAI, Azure OAI) based on task type and quality requirements

• Build and maintain IDM backend services — FastAPI, Celery/Redis, LangGraph runtime, CI/CD integration

• Surface agent observability — token usage, latency per hop, model selection audit trail, output quality metrics

Technical Skills Expected

• LangGraph — production-grade stateful graph design, interrupt/resume, shared memory, conditional edges

• LLM APIs — Anthropic Claude, OpenAI, Azure OpenAI; tool use, structured outputs, prompt construction at scale

• Python — async, FastAPI, Pydantic, Celery, Redis

• Prompt engineering — few-shot design, chain-of-thought, output parsers, self- consistency, reflection loops; not just RAG chat patterns

• Metadata-driven architecture — YAML config-driven generation, schema inference, column-level lineage design

• MCP server design and tool registration

• Vector stores and RAG

• Claude Code — experience using Claude Code as an agentic coding harness

• SKILL.md / prompt library design — ability to design and maintain skill files that encode conversion rules, output constraints, and few-shot patterns as versioned, reusable assets loaded by the harness at runtime

Apply