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At Teradata, we believe that people thrive when empowered with better information. That’s why we built the most complete cloud analytics and data platform for AI. By delivering harmonized data, trusted AI, and faster innovation, we uplift and empower our customers—and our customers’ customers—to make better, more confident decisions. The world’s top companies across every major industry trust Teradata to improve business performance, enrich customer experiences, and fully integrate data across the enterprise.
Job Responsibility:
Own the long-range architectural roadmap for elastic compute across the Teradata Cloud platform, including dynamic resource provisioning, multi-tenant workload isolation, and adaptive query scheduling for AI and analytics workloads
Lead a team of Senior Staff and Staff Architects, setting technical standards, driving design reviews, and cultivating a culture of engineering excellence and continuous improvement
Partner with CPO and ELT-1 engineering leaders to align elastic compute investments with Teradata's Artemis, Agentic Platform, and MCP Integration product priorities
Represent Core Platform architecture in executive and customer-facing forums
articulate compute strategy to Board-level audiences, enterprise accounts, and strategic partners
Drive a 10x productivity agenda across the architecture function through structured AI tool adoption—including AI-assisted design review, generative documentation, and automated performance regression analysis
Define the talent and capability model for the elastic compute architecture discipline
partner with Talent Acquisition to attract, assess, and onboard world-class architects globally
Establish governance frameworks, architectural review boards, and cross-functional working groups to ensure elastic compute decisions are made with speed and rigor
Identify and manage technical debt, platform risk, and capacity planning across the compute layer
present risk posture and mitigation roadmaps to senior leadership
Apply foundational AI skills to explore and implement ways AI can enhance productivity, innovation, and impact across our workforce
Requirements:
15+ years of progressive experience in cloud infrastructure or distributed systems engineering, including 5+ years in a senior architectural or engineering leadership role
Proven track record of setting multi-year technical strategy for large-scale, commercially deployed cloud platforms with global enterprise customers
Deep knowledge of elastic compute architectures—autoscaling, multi-cloud resource management, containerization, and workload scheduling—at petabyte and petaflop scale
Experience driving AI-powered productivity initiatives within engineering organizations, including measurable outcomes from AI tool adoption programs
Exceptional executive communication and stakeholder management skills, with a demonstrated ability to influence at the C-suite and Board level
Prior experience as a chief architect or distinguished engineer at a cloud infrastructure company, major database vendor, or hyperscaler
Familiarity with Teradata Cloud architecture, MPP systems, or enterprise data warehousing platforms
Experience managing globally distributed architecture teams and operating across cultural and time zone boundaries
Background in FinOps, cloud cost governance, or commercial engineering (understanding how compute cost flows to product pricing)
A track record of building AI-forward engineering cultures—where teams routinely use AI assistants, automated code review, and AI-generated documentation as standard practice
Demonstrated commitment to building diverse, equitable engineering teams with a strong personal brand as a technical leader
Nice to have:
Prior experience as a chief architect or distinguished engineer at a cloud infrastructure company, major database vendor, or hyperscaler
Familiarity with Teradata Cloud architecture, MPP systems, or enterprise data warehousing platforms
Experience managing globally distributed architecture teams and operating across cultural and time zone boundaries
Background in FinOps, cloud cost governance, or commercial engineering (understanding how compute cost flows to product pricing)
A track record of building AI-forward engineering cultures—where teams routinely use AI assistants, automated code review, and AI-generated documentation as standard practice
Demonstrated commitment to building diverse, equitable engineering teams with a strong personal brand as a technical leader