The Staff Data Architect is part of GE Vernova Enterprise Analytics and plays a critical leadership role in designing and governing enterprise-scale data architectures that enable analytics, AI, and GenAI solutions. This role supports the GEV Enterprise and Head Quarters domains/functions by ensuring data is well-modeled, trusted, scalable, and AI-ready.
Reporting to the Enterprise/HQ Analytics and AI Leader (or Data Architecture Leader), the Staff Data Architect partners closely with analytics product managers, data engineering, AI/ML/GenAI teams, and business stakeholders. This role owns the end-to-end data architecture, from source systems through curated layers, enabling advanced analytics, operational reporting, and AI-driven insights.
Enterprise & Domain Data Architecture
Define and own enterprise data architecture standards, patterns, and best practices aligned with GE Vernova’s analytics and AI strategy.
Lead conceptual, logical, and physical data modeling across key enterprise domains, including:
Finance (GL, FP&A, cost, profitability)
Sourcing & Procurement
Treasury & Cash Management
Supply Chain & Logistics
Translate complex business processes into reusable, governed, and scalable data models
Data Modeling & AI-Ready Data Design
Design analytics-optimized and AI-ready data models, including dimensional, data vault, and lakehouse patterns.
Ensure data structures support:
Business intelligence and advanced analytics
Machine learning and GenAI use cases
Feature engineering and model lifecycle needs
Partner with AI/ML teams to ensure data is fit-for-purpose for predictive, prescriptive, and generative solutions.
Platform & Technology Leadership
Architect and guide solutions on the Databricks Lakehouse platform, including:
Bronze, Silver, and Gold data layers
Unity Catalog and enterprise data governance
Performance, scalability, and cost optimization
Collaborate with cloud and platform teams to ensure architectures are secure, resilient, and compliant
Evaluate and influence adoption of emerging analytics, AI, and GenAI technologies.
Source Systems & Integration
Analyze and document source application data models (ERP, CRM, PLM, TMS, WMS, Finance systems).
Define integration and data pipeline patterns that ensure data quality, lineage, and traceability
Partner with data engineering teams to guide ingestion, transformation, and orchestration strategies.
Governance, Quality & Stewardship
Embed data governance, metadata, master data alignment, and lineage into all architectural designs.
Establish standards for data quality, consistency, security, and regulatory compliance
Act as an architectural authority and data steward, reviewing and approving designs across programs.
Leadership & Collaboration
Serve as a technical thought leader and mentor for architects, engineers, and analytics teams.
Collaborate with Analytics Product Managers to align architecture with business roadmaps and priorities.
Communicate architectural decisions clearly to technical and non-technical audiences.
Influence prioritization, architectural trade-offs, and long-term platform strategy.
Required Skills and Qualifications
Bachelor’s degree in Computer Science, Engineering, Data, or other STEM disciplines
10+ years of experience in data architecture, data modeling, or enterprise analytics platforms
Deep expertise in data modeling across finance, sourcing, treasury, logistics, and operations domains.
Strong understanding of ERP, CRM, PLM, and finance system data structures
Hands-on experience with Databricks and modern lakehouse architectures.
Proven experience designing AI/ML- and GenAI-ready data solutions
Experience with cloud data platforms (Azure preferred; AWS/GCP acceptable).
Strong knowledge of data governance, metadata, data quality, and security
Excellent communication skills with the ability to translate complex data concepts into business-aligned outcomes.
Demonstrated leadership and influence across cross-functional teams.
Preferred Qualifications
Master’s degree in a relevant technical or analytics field
Experience supporting enterprise-scale AI, ML, or GenAI initiatives
Familiarity with data mesh, data fabric, or domain-oriented architecture
Experience working in agile, product-based delivery models
Relevant cloud, data, or analytics certifications
Relocation Assistance Provided: Yes
GE Vernova is a purpose-built energy technology company on a mission to electrify to thrive and decarbonize the world.
It is made up of three businesses -- Power, Wind, and Electrification -- with focus on accelerating the path to more reliable, affordable, and sustainable energy, while helping our customers power economies and deliver the electricity that is vital to health, safety, security, and improved quality of life.
The world needs more energy, smarter energy. With energy demand expected to grow by more than 50% in the next 20 years, we are continuously innovating to meet the moment…like we have for the past 130 years. The Energy of Change and relentless optimism are what drive us – it’s about never giving up and seeing what’s possible so that we deliver the energy technologies the world needs right now and for generations to come.
GE Vernova’s attitude and edge is embedded in its name. We retain our treasured legacy, “GE,” as an enduring and hard-earned badge of quality and ingenuity. “Ver” / “verde” signal Earth’s verdant and lush ecosystems. “Nova,” from the Latin “novus,” nods to a new, innovative era of lower carbon energy that GE Vernova will help deliver.
Together, we have the energy to change the world.
