Job description

FEQ427R441 Sr. Solutions Architect The Role As a Sr. Solutions Architect, you are an expert-level technical leader responsible for the organization's most complex customer engagements. You drive consumption strategy, own executive-level relationships, and serve as the definitive technical authority for your accounts. You have declared your archetype—a recognized technical specialization that makes you a force multiplier across your team and region. You operate at the intersection of deep technical expertise, strategic account planning, and executive influence. 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 Interview Process: Recruiter Screen → Hiring Manager Screen → Design and Architecture Interview → Live Coding Assessment → Build, Demo, Pitch! Presentation → Reference Check Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected base salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipated utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here . Zone 1 Pay Range $219,100 — $301,300 USD Zone 2 Pay Range $219,100 — $301,300 USD Zone 3 Pay Range $219,100 — $301,300 USD Zone 4 Pay Range $219,100 — $301,300 USD About Databricks Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn , X , YouTube , and Instagram . Benefits At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here . Our Commitment to Diversity and Inclusion At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics. Compliance If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.

Requirements

Must-haves

FEQ427R441 Sr. Solutions Architect The Role
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

Nice-to-haves

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

Application prep

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