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Solutions Architects lead the adoption of Databricks' platform, consult on big data architecture, and develop solutions for customers. This role involves technical leadership, prototyping, and building reference architectures while collaborating with sales and technical teams.

Design and build systems for service communication across clusters, focusing on API gateways, service discovery, and overload protection.

Lead and grow a regional Lakebase specialist sales team to drive adoption of Databricks for operational, real-time, and transactional workloads. Own regional revenue targets and pipeline, coach specialists on deal strategy and technical qualification, execute developer/platform sales motions, engage senior technical executives and partners, and provide field feedback to product and GTM teams.

Lead architecture and hands-on development of AI-powered support automation and agentic workflows to reduce time-to-mitigate, improve quality, and scale Support. Own technical vision, implement observability and rollback mechanisms, align roadmaps across teams, and mentor engineers to ensure reliability and maintainability.

Design, build, and scale Databricks AI Runtime for large-scale GPU training. Lead architecture and implementation of multi-node orchestration, scheduling, checkpointing, resilience, throughput optimization, observability, and developer tooling. Mentor engineers, partner with product and research, and deliver high-impact production rollouts supporting thousands of accelerators and diverse model workloads.

Lead transformation of global travel, expense, and corporate spend programs into a digital-first, automated model. Build scalable T&E strategy, oversee travel operations, manage suppliers and corporate card programs, implement AI-enabled expense automation and controls, ensure compliance and audit readiness, partner with cross-functional teams, and build a high-performing global team.

Perform inbound and outbound prospecting to build pipeline, partner with sales to develop territory strategy, identify Databricks use cases to grow consumption, and deliver a strong customer experience through solution-focused outreach and follow-up.

Drive architecture and implementation of Databricks AI Runtime for large-scale GPU training. Build scheduling, distributed training performance, resilience, observability, and developer-facing APIs/CLI. Improve GPU utilization, fault tolerance, and multi-node orchestration. Lead cross-team initiatives, mentor engineers, and deliver high-impact platform features supporting thousands of accelerators and long-running jobs.

Build and productionize customer-facing data and AI solutions on the Databricks platform. Own architecture and design decisions, develop end-to-end data pipelines and applications, integrate machine learning models, and guide enterprise customers through implementation and adoption. Collaborate with engineering, product, support, project managers, and customer stakeholders while delivering projects, documenting solutions, resolving issues, and creating reusable frameworks. Travel to customers approximately 20% of the time.

Lead Databricks’ Learning initiative across self-paced and enterprise-managed learning products. Define technical and product strategy, own roadmap and delivery from 0-to-1 through large-scale adoption, establish engineering excellence, and partner cross-functionally with R&D, Learning, Marketing, and Field Engineering. Manage approximately 12 engineers while scaling the organization and building AI-powered learning systems, interactive labs, identity, sandboxing, provisioning, and distributed infrastructure for millions of learners.