Senior Principal Enterprise Data Architect, AI Data Transformation

GE Appliances, a Haier company; New York (NY); Hybrid; USD 170,000 - 210,000; Full time

Job summary

GE Appliances, a Haier company, is seeking a Senior Principal Enterprise Data Architect, AI Data Transformation, to lead the enterprise data layer across global operations. You will design AI-ready data architectures, governance frameworks, and vector data pipelines that enable reliable AI copilots and analytics.

You will partner with IT, product engineering, data science, and business leaders to align technology investments with strategic AI goals, enforce data contracts, and drive

Qualifications

• Bachelor's degree in CS/DS/IS/Math/Engineering required.
• Master's degree in CS/DS/AI strongly preferred.
• 15+ years of experience in data roles, with at least 5 years in enterprise data architecture.
• 3+ years designing and building AI/ML data infrastructure (feature stores, vector databases, model serving).
• Experience with ERP/PLM/IoT data in large enterprises is a plus.

Responsibilities

• Lead the enterprise data layer enhancement and AI-first data pipelines across R&D, supply chain, operations, and customer experience.
• Define and govern the Enterprise AI Data Architecture Blueprint and AI data readiness framework.
• Architect and deploy vector databases and embedding pipelines for AI models and copilots.
• Define data contracts, metadata management, and lineage to ensure semantic consistency and regulatory compliance.
• Align data architecture decisions with regulatory requirements while enabling AI agility.

Skills

Enterprise Data Architecture

AI Data Infrastructure

TOGAF/Zachman

Education

Bachelor's degree in CS/DS/IS/Math/Engineering

Master's degree in CS/DS/AI

Tools

BigQuery

Vector databases

Data governance tools

Job description

At GE Appliances, a Haier company, we come together to make “good things, for life.” As the fastest-growing appliance company in the U.S., we’re powered by creators, thinkers and makers who believe that anything is possible and that there’s always a better way. We believe in the power of our people and in giving them the freedom to explore, discover and build good things, together.

The GE Appliances philosophy, backed by three simple commitments defines the way we work, invent, create, do business, and serve our communities: we come together, we always look for a better way, and we create possibilities.

Candidates must be legally authorized to work in the United States at the time of hire and must be able to maintain such authorization without current or future employer or school sponsorship. GE Appliances will not sponsor employment-based visas for this position now or in the future.

Interested in joining us on our journey?

*Open to Remote/Hybrid Candidates*

The Senior Principal Enterprise Data Architect – AI Data Transformation will serve as a strategic partner and governance leader within the Enterprise Architecture (EA) team of our global enterprise. This role combines advanced enterprise data architecture discipline with deep expertise in Artificial Intelligence infrastructure and Data Science enablement to plan, design, deploy, and execute technology solutions aligned to the organization's strategic roadmap.

The incumbent will be instrumental in operationalizing complex initiatives by significantly enhancing, evolving, and optimizing the enterprise data layer to make every data asset—across our global operations, supply chain, customer touchpoints, and connected products—AI-ready, AI-consumable, and AI-trustworthy. This role will champion EA and AI data governance frameworks, drive Hoshin goal attainment, and serve as a key liaison between IT, business operations, product engineering, data science teams, and the EA team to ensure technology investments are aligned to enterprise standards and strategic AI objectives.

Position

Senior Principal Enterprise Data Architect, AI Data Transformation

Location

USA, Louisville, KYOther AL US, Other CT US, Other DC US, Other DE US, Other FL US, Other GA US, Other IL US, Other IN US, Other NC US, Other NE US, Other NH US, Other NJ US, Other NY US, Other OH US

How You'll Create Possibilities

AI Data Layer Enhancement & Transformation (40%)

• Lead the architectural enhancement and evolution of the enterprise data layer, applying AI-first design principles to unify data across the enterprise value chain (R&D, supply chain, operations, and customer experience).
• Define, publish, and maintain the Enterprise AI Data Architecture Blueprint—the authoritative reference governing how data flows from source systems (e.g. ERP, CRM, PLM, IoT platforms) through transformation layers to AI models and business outcomes.
• Design and operationalize an Enterprise AI Data Readiness Framework that continuously assesses, scores, and improves data assets across five core dimensions: Completeness, Consistency, Timeliness, Representativeness, and Fairness.
• Architect and deploy enterprise-grade vector database infrastructure and build enterprise embedding pipelines that transform structured records, enterprise documents, product manuals, and operational logs into high-quality vector representations.
• Define the complete data architecture for Large Language Model (LLM) integration, including Retrieval-Augmented Generation (RAG) architecture to support enterprise copilots, customer service, and operational workflows.
• Design ultra-low latency data serving architectures and event-driven AI data pipelines that feed live AI models in production (e.g., real-time operational analytics, predictive maintenance, and customer insights).
• Establish an enterprise Synthetic Data Generation capability to augment scarce datasets, generate privacy-safe alternatives to sensitive data, and simulate operational edge cases.

Enterprise Architecture Strategy & Governance (35%)

• Serve as a strategic partner and governance leader within the EA team, applying and evolving enterprise architecture frameworks (TOGAF, Zachman) with AI-era extensions tailored for a large-scale, complex enterprise environment.
• Architect modern cloud data warehouse and Lakehouse solutions (e.g. BigQuery) as the unified, ACID-compliant foundation for both analytical and AI/ML workloads on a single governed storage layer.
• Define and enforce data contracts between data producers (e.g., business operations, product engineering) and AI consumers across all domains to ensure schema, quality, freshness, and semantic consistency.
• Lead Master Data Management (MDM) strategy with AI entity resolution, enrichment, and disambiguation capabilities embedded in the MDM layer (covering Product, Material, Supplier, and Customer domains).
• Govern metadata management, data cataloging, and data lineage (e.g. Collibra) and design semantic/context data layers/Knowledge Graph infrastructure to map complex relationships between enterprise assets, suppliers, and business processes.
• Facilitate Architecture Review Board (ARB) processes for data and AI initiatives, ensuring alignment between project delivery and architectural intent.
• Align all data architecture decisions with regulatory and compliance requirements without compromising AI agility.

Data Science Enablement & Stakeholder Engagement (15%)

• Apply statistical expertise to validate data representativeness, distributions, class balance, and sampling strategies for AI training datasets (e.g., ensuring datasets accurately represent real-world operational realities).
• Serve as a trusted advisor and primary point of contact for business and IT stakeholders on AI data-governed initiatives.
• Build and maintain effective working relationships at all levels of DT Staff, Extended DT Staff, and business leadership.
• Proactively identify risks, issues, dependencies, and bottlenecks; implement mitigation strategies to keep teams moving forward.
• Partner with functional/business teams, DT teams, and other team members to solve problems collaboratively and deliver project objectives.

Data Engineering Oversight & Standards (10%)

• Provide architectural oversight and define enterprise standards for AI/ML-optimized data pipelines, guiding data engineering delivery teams from raw ingestion through feature engineering.
• Define the architecture and integration patterns for the Enterprise Feature Store as the central hub of reusable, versioned ML features.
• Establish DataOps and pipeline governance frameworks, guiding delivery teams on best practices for CI/CD, automated data quality testing gates, and infrastructure-as-code.
• Define architectural patterns for streaming and event-driven technologies to support high-velocity enterprise and IoT telemetry data.
• Elicit detailed business and architecture requirements, translating them into clear architectural guidelines and actionable work items for data engineering teams.

What You'll Bring to Our Team

Education

• Bachelor's degree in Computer Science, Data Science, Information Systems, Mathematics, Engineering, or a related technical field required.
• Master's degree in Computer Science, Data Science, Artificial Intelligence, or a related field strongly preferred.

Experience and Qualifications

• 15+ years of progressive experience in data-related roles, with a minimum of 5 years in Enterprise Data Architecture at enterprise scale.
• 3+ years of experience designing and architecting AI/ML data infrastructure (feature stores, vector databases, model serving layers, semantic layers).
• Proven track record of leading enterprise data transformation programs with measurable AI and ML outcomes delivered in production environments.
• Enterprise Industry Experience: Prior experience architecting data solutions involving complex supply chains, ERP (SAP/Oracle), PLM, or large-scale IoT/telemetry is preferred.
• Excellent oral and written presentation Skills
• Works independently with limited supervision and operates autonomously
• Working knowledge of enterprise architecture frameworks (e.g., TOGAF, Zachman)

Preferred Qualifications

• Experience working in both Agile and Waterfall delivery environments
• Project Management Professional (PMP) certification preferred
• TOGAF or other EA framework certification preferred

Our Culture

Our work is centered on our People and Culture as reflected in our Zero Distance philosophy and we recognize the importance of reaffirming our commitment to inclusion and diversity (I&D). This underscores our commitment to fostering an environment where every individual feels valued, connected, and empowered to contribute, while positioning our organization to adapt seamlessly to the evolving needs of our workforce and communities.

This reflects our dedication to creating solutions that: Empower colleagues by fostering an environment where all voices are heard, valued, and encouraged to contribute. Strengthen communities where we live and work. Reinforce a culture of belonging, purpose, and engagement. Reflect the diversity of the communities we serve through our workforce, products, and practices.

By further embedding Zero Distance into our People and Culture framework, we will continue to build a deeply connected organization. We are cultivating a culture of engagement, belonging, and connection, because while attracting new talent remains a priority, retention is a cornerstone of our strategy.

GE Appliances is a trust-based organization. It is important we offer our employees the flexibility they need to do their best work while balancing the needs of the business and individuals. When you join GE Appliances, you will have the opportunity to work with your leader to create a flexible work arrangement that balances the needs of the individual, team, and organization.

GE Appliances is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other characteristics protected by law.

GE Appliances participates in E-Verify and will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the U.S

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