Job Description Summary

Job Description

Enterprise & Domain Data Architecture

• Define and own enterprise data architecture standards patterns and best practices aligned with GE Vernovas 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

• Bachelors 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

• Masters 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.

Additional Information