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GM Financial

AVP Cloud Data Analytics Architecture

GM Financial

AVP Cloud Data Analytics Architecture leading cloud data architecture team at GM Financial. Responsible for scaling the Data & Analytics organization globally and deploying AI solutions.

Posted 7/22/2026full-timeIrving • Texas • 🇺🇸 United StatesLeadWebsite

Core Competencies

Role fit
Core Competencies

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

Demonstrates expertise in building enterprise-scale cloud data architecture and applications, with a strong focus on AI/ML solutions and compliance. Proven ability to lead cross-functional teams and integrate data across diverse environments while ensuring scalability, security, and cost optimization.

Highest-signal resume keywords
Cloud Data ArchitectureAI/ML Solutions DevelopmentAzure App ServiceDevOps and CI/CD ToolchainsLeadership Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
Cloud Application DevelopmentData OrchestrationAPI ManagementContainer OrchestrationMicroservice FrameworksProduction ML/AI SolutionsDatabricks MLAzure Machine LearningFinOpsCompliance Infrastructure
Soft Skills
CollaborationPartnership BuildingPlanning and Execution
Tools & Technologies
Azure DevOpsGitHubMicrosoft Copilot
Certifications & Qualifications
Microsoft Certified: Azure Solutions Architect ExpertAzure Data Engineer AssociateAzure AI Engineer AssociateDatabricks: Certified Data Engineer ProfessionalDatabricks: Machine Learning Professional
Industry Keywords
Cloud ComputingData AnalyticsAI EthicsData ProtectionResponsible AI

Tech Stack

Tools & technologies
AzureCloud

About the role

Key responsibilities & impact
  • Lead the cloud data architecture team and scale the Data & Analytics organization globally
  • Partner with business stakeholders to capture data, analytics, AI/ML, and GenAI requirements
  • Design, develop, and deploy Enterprise Cloud Data and AI solutions
  • Integrate data from disparate sources across cloud, hybrid, and multi-cloud environments
  • Deploy compliant infrastructure and support cloud resources (SRE)
  • Ensure cloud, data, ML, and AI platforms are scalable, secure, cost-optimized (FinOps), and compliant
  • Drive planning and execution while collaborating across cross-functional teams to deliver mission-critical outcomes
  • Build strong partnerships with cloud data architects, cloud platform teams, engineering teams, and vendors to scale global data and AI architecture and capabilities across the enterprise

Requirements

What you’ll need
  • 7–10 years building enterprise-scale cloud data architecture and applications to support ML/AI and analytics (required)
  • 7–10 years in cloud application development solutions (PaaS, SaaS, IaaS, Serverless, Data Orchestration, API Management) (required)
  • 7–10 years with scalable architectures using Azure App Service, API Management, serverless, container orchestration, microservice frameworks (required)
  • 7–10 years with DevOps and CI/CD toolchains (Azure DevOps, GitHub) (required)
  • 3+ years delivering production ML/AI solutions (preferred), including Databricks ML and Azure Machine Learning
  • Leadership: 7–10 years management or leadership experience (required)
  • High School Diploma or equivalent (required)
  • Bachelor’s Degree in a related field or equivalent work experience (required)
  • Master’s Degree in a related field (preferred)
  • Preferred Certifications (nice-to-have): Microsoft Certified: Azure Solutions Architect Expert, Azure Data Engineer Associate, Azure AI Engineer Associate Databricks: Certified Data Engineer Professional / Machine Learning Professional
  • Ability to use AI tools (e.g., Microsoft Copilot) to support daily work
  • Skills in evaluating AI outputs for accuracy, compliance, and bias
  • Experience integrating AI into workflows to improve efficiency or insights
  • Familiarity with AI assisted research, summarization, and content generation
  • Understanding of responsible AI use, including ethics and data protection

Benefits

Comp & perks
  • Generous benefits package available on day one to include: 401K matching
  • bonding leave for new parents (12 weeks, 100% paid)
  • tuition assistance
  • training
  • GM employee auto discount
  • community service pay
  • nine company holidays