Suggested rewrite: Led a cross-functional initiative that improved [business outcome] by [measurable result], demonstrating experience relevant to this role...
Solutions Architect – Digital Native Business (Geo)
- Remote from
- USA
- Salary
- USD 180k–247,500 / yr
- Department
- Software Engineering
- Employment
- Full Time
- Experience
- Director
- Published
- Apply before
- 6 Dec 2026
- Listing views
- 25
- Application actions
- 2
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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.
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.
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Sample interview questions
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.
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.
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.
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.
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.
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