Solutions Architect - Enterprise Platform Adoption

Databricks is the Data and AI company. Over 20,000 organizations worldwide—including 70% of the Fortune 500—rely on the Databricks Data + AI Platform (featuring Unity Catalog, Lakehouse, Lakeflow, Genie, and Agent Bricks) to build and scale data pipelines, analytics, AI applications, and autonomous agents.

As a Solutions Architect, you will lead the technical strategy for your assigned enterprise accounts—owning architectural design, driving platform adoption, and acting as a trusted advisor to customer engineering leads and technical directors. In this hands-on, pre-sales role, you will demonstrate live coding proficiency in Python and SQL, design production-grade data/AI architectures on public cloud infrastructure (AWS, Azure, or GCP), and establish a declared technical specialization (e.g., real-time streaming, ML/AI, governance, or migrations) within the Field Engineering organization.

Key Responsibilities

• Account Technical Strategy: Own the end-to-end technical strategy for accounts from initial discovery through architecture design, proof-of-concept (PoC), and production deployment.
• Architectural Leadership: Lead complex architecture reviews—designing scalable, production-grade solutions spanning data engineering, streaming, machine learning, and lakehouse patterns.
• Competitive Wins & Demos: Drive technical evaluation wins against competitive platforms (e.g., Snowflake, AWS native tools, Azure Synapse) by building and presenting custom Databricks solutions.
• Technical Specialization: Develop and declare an emerging technical specialization (archetype), becoming a domain go-to expert for internal teams.
• Cross-Functional Orchestration: Coordinate Specialist Solutions Architects (SSAs), Data Science Architects (DSAs), and partner ecosystem resources to deliver comprehensive technical solutions.
• Product Feedback Loop: Collect structured customer requirements and competitive insights to directly influence the Databricks product roadmap.

Requirements

Technical Skills & Experience

• 6+ years of experience in solutions architecture, data engineering, technical pre-sales, or a senior hands-on technical architecture role.
• Hands-On Coding Proficiency: Strong live coding, debugging, and solution-building skills in Python and SQL.
• Deep expertise in distributed data systems architecture: scalable ETL pipelines, real-time streaming, lakehouse design patterns, and cloud-native data infrastructure.
• Proficient on the Databricks Platform (or demonstrated ability to achieve proficiency rapidly).
• Practical experience with public cloud platforms (AWS, Azure, or GCP), including infrastructure automation, security, and governance models.

Communication & Process

• Proven experience leading technical whiteboarding sessions, design reviews, and architectural trade-off discussions with enterprise technical leaders.
• Strong track record of driving platform adoption, usage expansion, and business consumption within accounts.
• Degree in Computer Science, Engineering, Mathematics, or a related quantitative discipline (or equivalent practical experience).

Preferred Qualifications

• Official Databricks Certifications (e.g., Databricks Certified Data Engineer, ML Professional, or Solutions Architect).
• Hands-on experience positioning against or migrating from competitive platforms (Snowflake, AWS Native, Azure Synapse).
• Prior background working at a data/AI software company or cloud hyper-scaler.
• Specific industry domain expertise (e.g., Financial Services, Healthcare, Retail, Media).

Total Rewards & Benefits

• Pay Transparency: Total compensation / OTE range of $180,000 – $247,500 USD + annual performance bonus + equity grants.
• Healthcare & Wellbeing: Comprehensive medical, dental, and vision insurance options for employees and dependents.
• Financial Security: 401(k) program with matching, flexible work arrangements, and paid parental leave.