Sr. Solution Architect , Data & AI
Listed on 2026-10-17
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IT/Tech
Cloud Computing: Infrastructure & Operations, Data Engineering
About Carrier Carrier Global Corporation, global leader in intelligent climate and energy solutions, is committed to creating innovations that bring comfort, safety and sustainability to life. Through cutting-edge advancements in climate solutions such as temperature control, air quality and transportation, we improve lives, empower critical industries and ensure safe transport of food, lifesaving medicines and more. Since inventing modern air conditioning in 1902, we lead with purpose: enhancing the lives we live and the world we share.
We continue to lead because of our world-class, inclusive workforce that puts the customer at the center of everything we do. For more information, visit or follow on Carrier social media at @Carrier.
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.
- 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
- 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.
- 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 Big Query, 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
- Lead architecture reviews and design governance…
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