Sr. Solutions Architect (Energy)

The Impact You Will Have

• Drive the technical and consumption strategy for the organization's most complex customer engagements, directly influencing platform adoption and revenue growth.
• Own senior-level technical relationships — serving as a trusted advisor on enterprise data and AI strategy
• Lead the most complex architecture engagements: multi-workload platforms, enterprise-wide migrations, real-time systems, and AI/ML at scale
• Operate as an Expert on the Databricks Platform with a declared archetype — actively mentoring others and driving horizontal impact across your team
• Develop and execute competitive strategies for your customers, positioning Databricks against incumbent and emerging platforms
• Orchestrate cross-functional teams (DSAs, SSAs, Partners, Product) to deliver enterprise-grade solutions
• Coach and develop junior SAs (L3–L5) on technical depth, customer engagement, and use case prioritization
• Contribute to Field Engineering thought leadership through customer-facing content, workshops, and community engagement

What We Look For

• 8+ years in solutions architecture, principal engineering, technical pre-sales leadership, or a senior customer-facing technical role
• Expert-level coding proficiency — Python, SQL, and ideally Spark/PySpark. You will complete a live coding assessment and a platform build during the interview
• Deep expertise in enterprise data architecture: distributed systems at scale, streaming/real-time, lakehouse design patterns, data governance frameworks, and cloud-native platforms
• Expert-level Databricks Platform knowledge (or equivalent depth in competing platforms with demonstrated rapid learning ability)
• Declared technical specialization with recognized depth — e.g., real-time architectures, ML/AI platforms, data governance, large-scale migrations, or industry-specific solutions
• Proven track record of driving consumption growth and platform adoption in large accounts
• Executive presence — ability to influence Directors, VPs, and C-level stakeholders on long-term data and AI strategy
• Experience leading competitive displacements and complex enterprise evaluations
• Strong strategic thinking — connecting technical architecture decisions to business outcomes and revenue impact
• Bachelor's or Master's degree in Computer Science, Engineering, or a quantitative discipline (or equivalent experience); advanced degrees are valued

Nice to Have

• Databricks certifications
• Prior experience at Databricks, Snowflake, AWS, Google, Microsoft, or a top-tier data/AI company
• Published thought leadership (blogs, conference talks, open source contributions)
• Industry vertical expertise with executive-level domain credibility