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Sr. Solutions Architect – Digital Native Business (Strategic Accounts)

AI Summary
Databricks is hiring a senior, customer-facing Solutions Architect to lead highly complex strategic accounts in its Digital Native Business segment. The role combines enterprise data and AI architecture, technical pre-sales leadership, account strategy, and executive stakeholder influence. The architect will guide large-scale migrations, real-time and streaming workloads, lakehouse platforms, governance, and AI/ML implementations while driving platform adoption. Success requires expert Python, SQL, and ideally Spark/PySpark skills, as well as the ability to mentor other solution architects and coordinate cross-functional teams.
Remote from
USA
Salary
USD 219,100–301,300 / yr
Employment
Full Time
Experience
Director
Published
Apply before
7 Dec 2026
Listing views
34
Application actions
3
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Opportunity details

About this role.

The Role

As a Sr. Solutions Architect, you are an expert-level technical leader responsible for the most complex strategic customer engagements within the Digital Native Business. 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)
  • Strategic account 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 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 anticipates 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.

Local 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.

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This job listing has been manually reviewed by the Jobicy Trust & Safety Team for compliance with our posting guidelines, including verification of the company's legitimacy, accuracy of job details, clarity of remote work policy, and absence of misleading or fraudulent content.

Role DNA

A quick view of the complexity, pace, ownership and collaboration implied by the job description.

Job Complexity

5/5
EasyHard

Pace & Pressure

5/5
RelaxedFast-paced

Autonomy Level

5/5
GuidedFull ownership

Communication Load

5/5
IndependentCollaborative
AI insightThis is an expert-level strategic architecture role involving complex enterprise systems, live coding, platform demonstrations, and executive-level account ownership. It requires both deep hands-on data-platform expertise and the ability to influence technical and commercial outcomes across major accounts.

Salary analysis

Estimated compensation compared with the broader US market for similar roles.

Estimated job median (per year)Market rate
$260,200
US market range (per year)$210k–$320k
AI insightThe yearly pay period is inferred from the job context; it was not explicitly stated by the employer. The employer discloses a USD 219,100–301,300 annual pay range; the yearly cadence is inferred from the US senior full-time professional role and the magnitude of the disclosed range, as no explicit pay period is stated. The midpoint is $260,200 per year. A reasonable estimated US market range for an expert strategic data/AI solutions architect is approximately $210,000–$320,000 annually, excluding bonus, commission, and equity.

Core skills

Skills and capabilities most closely associated with this opportunity.

Sample interview questions
How would you design a lakehouse platform for a large enterprise with batch, streaming, analytics, and machine-learning workloads?

I would begin with business outcomes, workload profiles, data domains, security requirements, and service-level objectives. I would propose a governed lakehouse design with layered data modeling, scalable ingestion for batch and streaming, centralized catalog and access controls, workload-specific compute policies, observability, and CI/CD. I would then create a phased adoption roadmap that prioritizes high-value use cases and measurable consumption milestones.

Describe how you would lead a competitive displacement of an incumbent data platform.

I would first map the incumbent's technical footprint, stakeholder priorities, cost drivers, risks, and unmet requirements. I would align a Databricks proof of value to concrete business outcomes, define measurable success criteria, and demonstrate differentiated capabilities through architecture, implementation, and executive storytelling. Throughout the engagement, I would coordinate sales, partners, product specialists, and customer champions to manage technical and organizational risk.

How do you approach executive conversations about a long-term data and AI strategy?

I focus on business priorities rather than beginning with technology features. I connect platform decisions to outcomes such as faster product delivery, improved governance, lower operational complexity, and scalable AI adoption, while clearly explaining trade-offs and investment stages. I use a concise roadmap, quantified value hypotheses, and governance principles to create alignment across technical and business leaders.

What practices would you use to ensure reliable real-time data pipelines at enterprise scale?

I would design for idempotency, schema evolution, checkpointing, replayability, data-quality validation, observability, and clear ownership of operational service levels. I would also separate ingestion, transformation, and serving concerns, define failure-handling procedures, and implement automated testing and deployment controls. Capacity planning and cost monitoring would be included from the beginning rather than added after production launch.

How would you mentor junior solutions architects working on complex customer engagements?

I would combine structured coaching with practical joint account work. This includes reviewing discovery plans and architectures, modeling executive communication, providing actionable feedback after customer meetings, and assigning progressively more complex responsibilities. I would also help them build depth in a technical specialization while teaching them to connect technical recommendations to adoption and business value.

This analysis is generated from the job description. Salary estimates, role characteristics and sample answers are guidance, not employer-provided facts.
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