Senior Principal Enterprise Data Architect, AI Focus

GE Appliances, a Haier company; New Jersey; Hybrid; USD 180,000 - 260,000; Full time

Job summary

GE Appliances, a Haier company, seeks a Senior Principal Enterprise Data Architect, AI Data Transformation, to lead enterprise AI data architecture and governance across our global operations. You will shape data readiness, vector infrastructure, and model-serving pipelines, partnering with IT, business, and data science to deliver AI-ready data assets.

The role emphasizes AI-centric data platforms, enterprise metadata, and alignment with regulatory and enterprise standards.

Qualifications

• 15+ years of progressive data roles with at least 5 years in enterprise data architecture.
• 3+ years designing AI/ML data infrastructure (feature stores, vector DBs, model serving).
• Experience with ERP/SAP/Oracle, PLM, or large-scale IoT/telemetry.
• Strong presentation, stakeholder management, and independent work style.

Responsibilities

• Lead AI data layer enhancement and transformation across enterprise data assets.
• Define and govern the Enterprise AI Data Architecture Blueprint and readiness framework.
• Architect AI data pipelines, vector databases, and LLM integration patterns (RAG).
• Oversee standards, metadata, data contracts, and data lineage with governance tools.
• Collaborate with IT, business, product, and data science teams to align initiatives.

Skills

Data architecture

AI/ML infra

Enterprise data transformation

TOGAF

Zachman

BigQuery

Education

Bachelor's degree in Computer Science, Data Science, Information Systems, Mathematics, Engineering, or related technical field

Master's degree in Computer Science, Data Science, AI or related field strongly preferred

Tools

Collibra

Vector databases

Enterprise data warehouse

Job description

GE Appliances, a Haier company, seeks a Senior Principal Enterprise Data Architect, AI Data Transformation, to lead enterprise AI data architecture and governance across our global operations. You will shape data readiness, vector infrastructure, and model-serving pipelines, partnering with IT, business, and data science to deliver AI-ready data assets.

The role emphasizes AI-centric data platforms, enterprise metadata, and alignment with regulatory and enterprise standards.