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# Data & Knowledge Architect

- **Company:** Everforth Apex
- **Location:** Chandler, AZ, United States
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Software Documentation, Information Systems, Data Governance, Metadata, Metadata Standards, Network Service, Unstructured Data, Indexer, Information Technology, Data Management, Machine Learning Operations, Data Pipelines
- **Published:** October 31, 2026
- **Apply:** https://www.dice.com/job-detail/335b2ab0-00b0-42f7-b993-469e5e37c827

## About the Role

Education: Bachelor's degree in Computer Science, Information Systems, Data Science, or a related technical field is preferred.

Experience: Documented experience engineering and managing both structured and unstructured data used for analytics, automation, search, or model-enabled solutions within a regulated enterprise environment.

Technical Skills: Proven expertise in data modeling and architecture, data governance protection, data management, and machine learning systems. Proficiency in designing scalable data pipelines, implementing data quality controls, and establishing lineage and metadata standards is required.

## Description

This position is responsible for developing, governing, and improving the data and knowledge foundations that support artificial intelligence and agentic capabilities across network services. The selected candidate will work across structured and unstructured data sources to ensure information is defined, organized, governed, and made available in a manner suitable for model consumption. This professional will establish standards, guidelines, and guardrails for how operational knowledge, documentation, configurations, telemetry, metadata, and other contextual assets are curated and prepared for trusted model use. Collaboration with product and service subject matter experts is essential to translate high-quality data and knowledge into reusable, AI-ready assets., * Develop and maintain data and knowledge assets that support AI and agentic use-cases, including both structured and unstructured sources.

 * Define and apply standards for how documentation, configurations, telemetry, metadata, policies, and operational knowledge should be organized and prepared for model consumption.
 * Partner with product and service subject matter experts to understand technologies, operational context, and domain-specific knowledge required to improve model grounding and decision quality.
 * Design and implement scalable methods for storing, governing, indexing, and retrieving context assets needed for enabled workflows and solutions.
 * Establish and improve preventative and detective controls that identify and reduce data quality, metadata quality, knowledge quality, and freshness issues before they affect downstream use.
 * Contribute to data quality remediation efforts by identifying upstream sources of issues, defining corrective actions, and improving the reliability of data at the source.
 * Define and maintain expectations for data ownership, lineage, freshness, stewardship, and governance across relevant data and knowledge domains.
 * Build and enhance pipelines, transformations, validation routines, and supporting services that improve the quality and accessibility of data and knowledge assets.
 * Support the creation of reusable templates, patterns, and guidance for knowledge artifacts, documentation standards, and context management practices.
 * Monitor and communicate the health, readiness, and quality of relevant data and knowledge assets, including issues, gaps, and remediation priorities.