FEQ227R273

While candidates in the listed location(s) are encouraged for this role, candidates in other locations will be considered. #CMEG

As a Solutions Architect, you will lead the technical strategy for your customers — owning architecture discussions, driving platform adoption, and serving as a trusted advisor to customer technical leads and architects. You combine deep technical expertise with strategic thinking to position Databricks as the foundation of your customers' data and AI strategy. You are developing a technical specialization (archetype) and are recognized 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 initial discovery through production deployment and consumption growth
• Lead complex architecture discussions — designing scalable, production-grade solutions spanning data engineering, ML/AI, and real-time analytics
• Serve as a trusted technical advisor to customer architects, engineering leads, and Directors
• Drive technical wins in competitive scenarios by demonstrating Databricks' differentiation through custom-built solutions
• Develop and declare an emerging technical specialization (archetype) — becoming a go-to resource for your team in that domain
• Orchestrate cross-functional resources (DSAs, SSAs, Partners) to deliver comprehensive solutions for complex customer needs
• Influence product direction by providing structured feedback on customer requirements and competitive gaps

What We Look For

• 6+ years in solutions architecture, data engineering, technical pre-sales, or a senior hands-on technical role
• Strong coding proficiency in Python and SQL — you must demonstrate live coding, debugging, and solution-building skills
• Deep expertise in distributed data systems architecture: designing scalable pipelines, streaming architectures, lakehouse patterns, and cloud-native data platforms
• Proficient on the Databricks Platform (or demonstrated ability to achieve proficiency rapidly) with a developing technical specialization in one area (e.g., real-time/streaming, ML/AI, data governance, migrations)
• Proven ability to lead architecture discussions with senior technical stakeholders — whiteboarding, design reviews, and trade-off analysis
• Experience with production deployments on public cloud (AWS, Azure, or GCP), including infrastructure, security, and governance considerations
• Track record of driving platform adoption and consumption growth within accounts
• Excellent communication skills — able to translate complex architectures into business value for both 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, Platform)
• Experience with competitive platforms (Snowflake, AWS native services, Azure Synapse) — understanding the landscape you'll position against
• Background in a data/AI company or cloud provider
• Industry domain expertise (Financial Services, Healthcare, Retail, Media, etc.)

Interview Process: Recruiter Screen → Hiring Manager Screen → Design and Architecture Interview → Live Coding Assessment → Build, Demo, Pitch! Presentation → Reference Check