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Solutions Architect – Digital Native Business (Geo)

AI Summary
Databricks is seeking a senior Solutions Architect to own technical strategy and platform adoption for digital-native customer accounts. The role combines customer-facing technical pre-sales work with hands-on solution design across data engineering, streaming, ML/AI, and cloud data platforms. The architect will lead design reviews, demonstrate custom Databricks solutions, coordinate specialist resources, and influence product direction through customer feedback. Candidates need at least six years of relevant experience, strong Python and SQL skills, distributed-systems expertise, and the ability to communicate architecture trade-offs to executive and engineering stakeholders.
Remote from
USA
Salary
USD 180k–247,500 / yr
Employment
Full Time
Experience
Director
Published
Apply before
6 Dec 2026
Listing views
25
Application actions
2
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Opportunity details

About this role.

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

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

$180,000—$247,500 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

4/5
RelaxedFast-paced

Autonomy Level

5/5
GuidedFull ownership

Communication Load

5/5
IndependentCollaborative
AI insightThis is a senior, customer-facing architecture position requiring deep practical expertise across distributed data systems, cloud platforms, Python, SQL, and ML/AI. Success also depends on independently leading high-stakes technical evaluations and translating complex designs into business value.

Salary analysis

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

Estimated job median (per year)Market rate
$213,750
US market range (per year)$175k–$260k
AI insightThe yearly pay period is inferred from the job context; it was not explicitly stated by the employer. The employer discloses a USD 180,000–247,500 yearly local pay range; the annual cadence is inferred from the magnitude and senior US professional-role context because no explicit pay period is stated. The stated range may represent salary for non-commissionable roles or on-target earnings for commissionable roles. Estimated US market compensation for comparable senior data and AI solutions architects is USD 175,000–260,000 per year.

Core skills

Skills and capabilities most closely associated with this opportunity.

Sample interview questions
How would you design a scalable lakehouse platform for a customer ingesting batch and real-time data?

I would begin with workload, latency, governance, and consumption requirements. I would propose layered ingestion and transformation pipelines, use managed streaming for low-latency sources, apply data-quality controls, and define security, lineage, and cost-management practices. I would validate the design through a small production-oriented proof of value with measurable performance and reliability criteria.

Describe how you would explain the value of a distributed data platform to a non-technical executive.

I would connect technical capabilities to business outcomes such as faster decision-making, lower operational cost, reduced data risk, and quicker delivery of AI products. I would avoid platform jargon, use a relevant customer workflow, quantify expected impact where possible, and clearly state the implementation path and success measures.

How do you approach a technical evaluation against a competing platform such as Snowflake or native cloud services?

I first identify the customer's decision criteria, existing architecture, and priority use cases rather than leading with feature comparisons. I then build a targeted demonstration that tests relevant requirements such as unified data and AI workflows, streaming performance, governance, developer productivity, and operational cost. I document trade-offs transparently and align technical findings to the customer's business goals.

What steps would you take when a production streaming pipeline is experiencing increasing latency?

I would inspect end-to-end metrics to isolate whether the bottleneck is source ingestion, processing, state management, storage, or downstream consumption. I would review partitioning, skew, batch sizing, autoscaling, checkpoint behavior, and expensive transformations, then test changes against representative traffic. Finally, I would add operational alerts and capacity thresholds to prevent recurrence.

Tell us about your approach to leading an architecture discussion with senior stakeholders who disagree on the solution direction.

I establish the shared business objective and make assumptions, constraints, risks, and decision criteria explicit. I present feasible options with clear trade-offs around scalability, security, cost, delivery time, and maintainability, using diagrams or a concise prototype where useful. I facilitate a decision based on evidence, document the rationale, and define follow-up actions and ownership.

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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