About this role.
Databricks is seeking a customer-facing Delivery Solutions Architect to lead post-sale technical delivery, adoption, and growth for startup and emerging enterprise accounts. The role combines distributed data and AI solution architecture with technical program leadership, executive stakeholder management, and commercial account strategy. The successful candidate will coordinate internal technical teams, guide use cases from technical win through production, and track customer health, usage, risks, and adoption. Core requirements include five or more years delivering complex Data and AI programs, Python, SQL, or Scala experience, and the ability to resolve high-stakes customer escalations. This is a remote US role with up to 30% travel.
Role DNA
A quick view of the complexity, pace, ownership and collaboration implied by the job description.
Job Complexity
5/5Pace & Pressure
5/5Autonomy Level
5/5Communication Load
5/5Salary analysis
Estimated compensation compared with the broader US market for similar roles.
Core skills
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Sample interview questions
I would begin with a discovery session to confirm business outcomes, technical scope, stakeholders, risks, success metrics, and target timeline. I would create a joint execution plan covering architecture decisions, onboarding, enablement, governance, production readiness, and adoption milestones. I would then coordinate Databricks specialists and customer teams, run regular health reviews, and escalate blockers early while keeping executive sponsors aligned on measurable value.
I would first establish a clear incident structure: confirm impact, assign technical owners, define communication cadence, and document immediate containment actions. I would communicate transparently with the executive sponsor in business terms, including the issue, customer impact, mitigation plan, and expected next update. After resolution, I would lead a retrospective with corrective actions, ownership, and preventive monitoring to rebuild confidence.
I map each workload or use case to an agreed business outcome, such as reduced pipeline runtime, improved decision speed, lower cloud cost, increased model deployment velocity, or greater user adoption. I define baselines and measurable KPIs before implementation, then report progress through usage, performance, reliability, and outcome metrics. This makes the technical roadmap understandable to both engineering leaders and business executives.
I consider workload patterns, data volume and velocity, reliability requirements, security and governance, cost controls, performance expectations, integration points, and operational ownership. I also evaluate how data engineering, analytics, machine learning, and governance teams will use the platform over time. The resulting design should be scalable, observable, secure, and aligned with the customer’s near-term priorities and long-term operating model.
I would use a transparent prioritization framework based on business value, strategic alignment, production readiness, dependencies, risk, customer commitment, and required effort. I would validate priorities with executive sponsors and technical owners, then maintain a roadmap that makes sequencing and tradeoffs explicit. Regular governance reviews would allow us to adjust priorities as customer needs, adoption signals, or risks change.
At Databricks, we are on a mission to empower our customers to solve the world’s toughest data problems by utilizing the Databricks Data Intelligence Platform. As a Delivery Solutions Architect (DSA), you will play an important role during this journey. You will collaborate with our sales and field engineering teams to accelerate the adoption and growth of the Databricks platform with Startup and Emerging Enterprise customers. You will also help ensure customer success by helping our most complex customers maximize the value they get out of our platform and their return on investment.
This is a hybrid technical and commercial role. It is commercial in the sense that you will drive growth in your assigned customers and use cases by leading your customers’ stakeholders, building executive relationships, orchestrating other focused/specialized teams within Databricks, and creating and driving plans and strategies for Databricks colleagues to build upon. It is technical in the sense that you will serve as the post-sale technical lead across all Databricks products. This requires you to use your skills and technical credibility to engage and communicate at all levels within an organization. You will report directly to a DSA Manager within the Field Engineering organization.
The impact you will have:
- Engage with Solutions Architects to understand the full use case demand plan for prioritized customers
- Lead the post-technical-win account strategy and execution plan for the majority of Databricks use cases within our most strategic accounts
- Be the accountable technical leader for specific use cases and customers across multiple selling teams and internal stakeholders, creating certainty from uncertainty and driving onboarding, enablement, go-live, and healthy consumption of the workloads the customer has chosen to run on Databricks
- Be the first contact for any technical issues or questions related to production/go live status of agreed upon use cases within an account, often spanning multiple use cases within the largest and most complex organizations
- Leverage Shared Services, User Education, Onboarding/Technical Services, and Support resources, and escalate to subject matter experts when work falls beyond your scope or expertise
- Create, own, and execute a point of view on how key use cases can be accelerated into production, coordinating with Professional Services (PS) resources on the delivery of PS Engagement proposals
- Partner with Databricks Product and Engineering teams on new product innovations, private previews, and upgrades
- Develop an execution plan spanning all customer-facing technical roles and teams across the following work streams:
- Main use cases moving from ‘win’ to production
- Enablement / user growth plan
- Product adoption (strategy and activities to increase adoption of Databricks’ Lakehouse vision)
- Organic needs for current investment (e.g. cloud cost control, tuning & optimization)
- Executive and operational governance
- Provide internal and external updates to your Technical GM — KPI reporting on usage and customer health, covering investment status, key risks, product adoption, and use case progression
What we look for:
- 5+ years of experience accountable for technical project / program delivery in Data and AI, with the ability to contribute to technical debate and design choices alongside customers
- Programming experience in Python, SQL or Scala
- Experience in a customer-facing pre-sales, technical architecture, customer success, or consulting role
- Understanding of solution architecture for distributed data systems
- Understanding of how to attribute business value and outcomes to specific project deliverable
- Technical program or project management, including accountability for accounts, stakeholders, and resources
- Experience resolving complex, high-stakes escalations with senior customer executives
- Experience conducting open-ended discovery workshops, creating strategic roadmaps, conducting business analysis, and managing delivery of complex programs/projects
- Track record of overachievement against quota, goals, or similar objective targets
- Bachelor’s degree in Computer Science, Information Systems, Engineering, or equivalent practical experience
- Can travel up to 30% when needed
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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