FEQ427R473

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.

The Impact You Will Have:

• 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
• Lead complex architecture discussions — designing production-grade solutions across data engineering, AI/ML, agentic systems, and real-time analytics
• Serve as a trusted technical partner to customer architects, engineering leads, and Directors — helping shape their data and AI journey on Databricks
• Develop an emerging technical specialization (archetype) — ideally in AI/ML, agentic architectures, or a related domain — becoming a go-to resource within your team
• Orchestrate cross-functional resources (DSAs, SSAs, Partners) to deliver end-to-end AI and data solutions for complex customer needs
• Provide structured feedback to product teams on customer requirements, AI capabilities, and competitive gaps

What We Look For:

• 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
• 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
• 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
• 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)
• Experience with production deployments on public cloud (AWS, Azure, or GCP), including security and governance considerations
• Track record of driving platform adoption and consumption growth — particularly across AI/ML and data analytics workloads
• Excellent communication skills — able to translate complex AI and data architectures into business value for technical and executive audiences
• Bachelor's or Master's degree in Computer Science, Engineering, or a quantitative discipline (or equivalent experience)

Nice to Have:

• Databricks certifications (Data Engineer, ML Associate/Professional, Platform)
• Experience with competitive platforms (Snowflake, AWS native services, Azure Synapse) — understanding the landscape you'll position against
• Background in an AI-first company, data platform vendor, or cloud provider
• Industry domain expertise, preferably in CPG and Manufacturing (Financial Services, Healthcare, Retail, Media, etc. also valued)