Senior Principal Enterprise Data Architect, AI Data Transformation

GE Appliances, Recreational Living

. Lead the architectural enhancement and evolution of the enterprise data layer using AI-first design principles across R&D, supply chain, operations, and customer experience .

Posted 10/27/2026full-timeUnited StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in Enterprise Data Architecture, AI/ML Data Infrastructure, and Data Governance, with a strong focus on architectural frameworks such as TOGAF and Zachman. Proven ability to lead data transformation initiatives and design scalable data solutions that align with business objectives and regulatory requirements.

Highest-signal resume keywords

Enterprise Data ArchitectureAI/ML Data Infrastructure DesignData Governance and ManagementTOGAF Framework ExpertiseData Transformation Leadership

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Data ArchitectureAI Data Readiness FrameworkVector Database InfrastructureEvent-Driven Data PipelinesDataOps GovernanceFeature Store ArchitectureSemantic Layer DesignData Quality TestingData CatalogingMaster Data Management

Soft Skills

Excellent Presentation SkillsIndependent Work CapabilityRelationship Building

Tools & Technologies

CollibraBigQueryERP (SAP/Oracle)PLM SystemsIoT Telemetry

Certifications & Qualifications

PMP CertificationTOGAF Certification

Industry Keywords

Data Transformation ProgramsAI and ML OutcomesRegulatory ComplianceAgile and Waterfall MethodologiesData Contracts

Tech Stack

Tools & technologies

BigQueryCloudERPIoTOraclePMP

About the role

Key responsibilities & impact

Lead the architectural enhancement and evolution of the enterprise data layer using AI-first design principles across R&D, supply chain, operations, and customer experience
Define, publish, and maintain the Enterprise AI Data Architecture Blueprint
Design and operationalize an Enterprise AI Data Readiness Framework assessing Completeness, Consistency, Timeliness, Representativeness, and Fairness
Architect and deploy enterprise-grade vector database infrastructure and embedding pipelines
Define data architecture for LLM integration, including Retrieval-Augmented Generation architecture
Design ultra-low-latency data serving architectures and event-driven AI data pipelines
Establish enterprise Synthetic Data Generation capabilities
Apply and evolve enterprise architecture frameworks including TOGAF and Zachman
Architect cloud data warehouse and Lakehouse solutions such as BigQuery
Define and enforce data contracts between data producers and AI consumers
Lead Master Data Management strategy with AI entity resolution, enrichment, and disambiguation
Govern metadata management, data cataloging, and data lineage using tools such as Collibra
Design semantic/context data layers and Knowledge Graph infrastructure
Facilitate Architecture Review Board processes for data and AI initiatives
Align data architecture decisions with regulatory and compliance requirements
Validate data representativeness, distributions, class balance, and sampling strategies for AI training datasets
Advise business and IT stakeholders on AI data-governed initiatives
Build working relationships with DT Staff, Extended DT Staff, and business leadership
Identify risks, issues, dependencies, and bottlenecks and implement mitigation strategies
Provide architectural oversight and enterprise standards for AI/ML-optimized data pipelines
Define architecture and integration patterns for an Enterprise Feature Store
Establish DataOps and pipeline governance frameworks covering CI/CD, automated data quality testing, and infrastructure-as-code
Define streaming and event-driven architecture patterns for enterprise and IoT telemetry data
Elicit business and architecture requirements and translate them into architectural guidelines and actionable work items

Requirements

What you’ll need

Legally authorized to work in the United States at the time of hire and able to maintain authorization without current or future employer or school sponsorship
Bachelor's degree in Computer Science, Data Science, Information Systems, Mathematics, Engineering, or a related technical field required
15+ years of progressive experience in data-related roles
Minimum of 5 years in Enterprise Data Architecture at enterprise scale
3+ years of experience designing and architecting AI/ML data infrastructure, including feature stores, vector databases, model serving layers, and semantic layers
Proven track record of leading enterprise data transformation programs with measurable AI and ML outcomes delivered in production environments
Excellent oral and written presentation skills
Ability to work independently with limited supervision and operate autonomously
Working knowledge of enterprise architecture frameworks such as TOGAF and Zachman
Experience involving complex supply chains, ERP (SAP/Oracle), PLM, or large-scale IoT/telemetry preferred
Experience in both Agile and Waterfall delivery environments preferred
PMP certification preferred
TOGAF or other EA framework certification preferred
Master's degree in Computer Science, Data Science, Artificial Intelligence, or a related field strongly preferred

Benefits

Comp & perks

Open to Remote/Hybrid Candidates
Flexible work arrangement created with the leader to balance individual, team, and organizational needs
Equal Opportunity Employer
Disability accommodations available for applicants
Employment authorization support through E-Verify (no employment-based visa sponsorship)