Solutions Architect - CPG and Manufacturing

<p>FEQ427R473</p> <p>As a Solutions Architect, you will contribute to the technical strategy for your customers — owning architecture discussions, driving platform adoption, and serving as a trusted technical partner to customer architects and engineering leads. You combine deep technical expertise with a hands-on builder mindset to position Databricks as the foundation of your customers' data and AI strategy. You are developing a technical specialization (archetype) and are becoming a go-to resource within your team for depth in a specific domain.</p> <h3>The Impact You Will Have:</h3> <ul> <li>Own the end-to-end technical strategy for your accounts — from discovery through production deployment — driving competitive wins by building differentiated AI and data solutions that accelerate consumption growth</li> <li>Lead complex architecture discussions — designing production-grade solutions across data engineering, AI/ML, agentic systems, and real-time analytics</li> <li>Serve as a trusted technical partner to customer architects, engineering leads, and Directors — helping shape their data and AI journey on Databricks</li> <li>Develop an emerging technical specialization (archetype) — ideally in AI/ML, agentic architectures, or a related domain — becoming a go-to resource within your team</li> <li>Orchestrate cross-functional resources (DSAs, SSAs, Partners) to deliver end-to-end AI and data solutions for complex customer needs</li> <li>Provide structured feedback to product teams on customer requirements, AI capabilities, and competitive gaps</li> </ul> <h3>What We Look For:</h3> <ul> <li>6+ years in solutions architecture, data engineering, data science/AI, or technical pre-sales — with a strong track record of hands-on solution building and customer-facing technical leadership</li> <li>Deep expertise in modern data and AI architectures — lakehouse design, scalable pipelines, real-time/streaming, and cloud-native platforms — with the ability to lead architecture discussions with senior stakeholders through whiteboarding, design reviews, and trade-off analysis that connect data foundations to AI/ML outcomes</li> <li>Strong understanding of AI/ML concepts, agentic architectures, and ontology design — including experience with compound AI systems, autonomous agent frameworks, knowledge graphs, and semantic data models that enable intelligent, context-aware applications</li> <li>Proficient on the Databricks Platform (or demonstrated ability to achieve proficiency rapidly) with a developing technical specialization in one area (e.g., AI/ML, agentic systems, real-time/streaming, data governance, migrations)</li> <li>Experience with production deployments on public cloud (AWS, Azure, or GCP), including security and governance considerations</li> <li&g