Data and Architect

Data and Knowledge Architect Job#: 3056265

Job Description:

Data and Knowledge Architect

Location:

Chandler, Arizona (Hybrid)

Role Overview This role is responsible for leading the design, governance, and continuous improvement of the data and knowledge foundations that support AI and agentic capabilities across Network Services. The individual in this role works across both structured and unstructured data sources to ensure information is defined, organized, governed, and made available in a manner suitable for trusted AI consumption. This position provides senior-level leadership in defining standards, guidelines, and guardrails for how operational assets are curated, controlled, and prepared for model use.

Key Responsibilities Lead the design and improvement of data and knowledge assets that support AI and agentic use-cases across Network Services.

Define and maintain standards for how documentation, configurations, telemetry, metadata, policies, and operational knowledge should be organized and prepared for AI consumption.

Partner with subject matter experts to understand network technologies, operational context, and domain-specific knowledge.

Design and guide scalable methods for storing, governing, indexing, validating, and retrieving context assets for AI-enabled solutions.

Establish and evolve preventative and detective controls that identify and reduce data quality, metadata quality, and knowledge quality issues.

Lead remediation efforts for data and knowledge quality issues by identifying root causes and defining corrective actions.

Define expectations for ownership, stewardship, lineage, freshness, and governance across relevant data and knowledge domains.

Build or guide the development of pipelines, transformations, and validation routines that improve the quality and accessibility of AI-relevant context assets.

Work across engineering, architecture, operations, and governance teams to ensure data and knowledge practices align with enterprise controls and standards.

Monitor and communicate the health, readiness, and quality of AI-relevant data and knowledge assets.

Required Qualifications Experience engineering and governing both structured and unstructured data for analytics, automation, search, or AI-enabled solutions.

Advanced understanding of data modeling, transformation, storage, indexing, retrieval, and metadata management patterns.

Demonstrated ability to define enterprise-ready standards for data, documents, and knowledge artifacts.

Experience establishing and improving data quality, metadata quality, and knowledge quality controls.

Knowledge of preventative and detective controls used to identify and remediate issues related to data and documentation quality.

Experience with knowledge sources such as policies, standards, configurations, telemetry, and operational documentation.

Ability to work with subject matter experts to interpret operational knowledge and translate it into reusable, governed assets.

Working understanding of network technologies, infrastructure concepts, and service models.

Experience defining data ownership, stewardship, lineage, and governance expectations in a regulated enterprise environment.

Familiarity with AI-oriented data preparation concepts, including grounding, retrieval-readiness, and context structuring.

Ability to design scalable approaches for storing, governing, and retrieving contextual assets used by AI-enabled workflows.

Experience leading or influencing cross-functional work across engineering, architecture, operations, and governance stakeholders.

Strong written and verbal communication skills.

Preferred Qualifications Experience mentoring less senior engineers on data engineering, knowledge engineering, and control design practices.

Ability to…