Job Description

The Data & AI Solution Architect is a senior technology leader responsible for leading the architecture, design, governance, and technical oversight of Carrier's enterprise cloud transformation initiatives, with primary responsibility for the migration of data platforms, analytics workloads, and AI solutions from AWS to Google Cloud Platform (GCP). This role establishes cloud architecture standards, defines target-state roadmaps, creates governance frameworks, and ensures scalable, secure, resilient, and cost-effective solutions across enterprise data, analytics, and AI ecosystems.

The position serves as a trusted advisor to business and technology leadership, guiding engineering teams through cloud modernization efforts, driving adoption of GCP best practices, and enabling long-term platform simplification, operational excellence, and innovation. The architect will collaborate closely with business stakeholders, delivery teams, cloud platform teams, security, and external partners to ensure successful execution of strategic transformation programs.

Key Responsibilities

Cloud Transformation & Architecture Leadership

• Lead the architecture strategy and technical governance for enterprise cloud modernization initiatives
• Define target-state architectures, migration roadmaps, and transition strategies for AWS-to-GCP transformation programs
• Establish enterprise cloud architecture standards, design principles, reference architectures, and reusable pattern
• Drive technology rationalization, platform modernization, and reduction of technical debt across data and analytics ecosystems
• Evaluate emerging cloud technologies and provide architecture recommendations aligned with business objectives

AWS-to-GCP Migration Leadership

• Lead architecture planning and execution for migration of data platforms, data products, analytics workloads, and AI solutions to GCP
• Define migration approaches, landing zones, modernization patterns, and workload transition frameworks
• Guide engineering teams on migration best practices, risk mitigation strategies, and operational readiness
• Ensure successful migration of applications, data pipelines, warehouses, lakehouse platforms, and AI services while minimizing business disruption
• Establish migration governance, review processes, and architecture quality gates.

Data, Analytics & AI Platform Architecture

• Architect scalable and secure data lake, lakehouse, analytics, and AI platforms on GCP
• Define enterprise standards for data integration, batch and streaming pipelines, API enablement, metadata, governance, and data quality
• Guide architecture decisions involving BigQuery, Vertex AI, Dataproc, Dataflow, Pub/Sub, and broader GCP ecosystem services
• Support AI, Machine Learning, Generative AI, and advanced analytics initiatives through scalable platform design and governance
• Enable reusable, AI-ready data products and shared platform capabilities across business units

Architecture Governance & Solution Assurance

• Lead architecture reviews and design governance processes for cloud and data initiatives
• Validate solution designs for scalability, security, reliability, availability, performance, and maintainability
• Establish cloud security, compliance, privacy, and operational standards in partnership with cybersecurity teams
• Drive FinOps practices and cloud cost optimization strategies.
• Ensure alignment with enterprise architecture standards and platform engineering best practices

Stakeholder Engagement & Technical Leadership

• Partner with business, product, engineering, cloud platform, security, and operations teams to align technology strategy with business goals
• Act as the primary architecture advisor for cloud transformation programs and executive stakeholders
• Mentor architects and engineering teams on GCP architecture, cloud-native design, and modernization best practices
• Build organizational capability and establish long-term GCP architecture expertise across the enterprise

Required Qualifications

• Bachelor’s Degree in engineering or technical discipline
• 10+ years of experience in Enterprise Architecture, Solution Architecture, Cloud Architecture, or Data Platform Architecture

Preferred Qualifications

• Master’s degree
• 5+ years designing and delivering large-scale cloud solutions on GCP, AWS, or Azure
• Knowledge of Google Cloud Platform such as BigQuery, Vertex AI, Dataflow, Dataproc, Pub/Sub, Cloud Storage, IAM, VPC, Monitoring
• Experience with Lakehouse Architectures, Data Warehousing, Data Integration, Streaming, Data Governance
• AI & ML: Vertex AI, Machine Learning Platforms, Generative AI, MLOps
• Platform Engineering: Kubernetes, Terraform, CI/CD, DevSecOps, Observability
• Architecture & Governance: Enterprise Architecture, Architecture Review Boards, Reference Architectures, Technology Standards
• Demonstrated success governing large-scale data, analytics, and AI platforms.
• Experience working in global organizations and influencing cross-functional technology teams