About this role.
This Delivery Solutions Architect role leads post-sale technical strategy, adoption, and production delivery for complex Databricks customer use cases. The position combines data and AI solution architecture with program leadership, executive stakeholder management, and commercial account growth. It coordinates internal engineering, professional services, support, onboarding, and education teams to move workloads from technical win through go-live and healthy consumption. Candidates need hands-on credibility in distributed data systems and Python, SQL, or Scala, alongside experience managing complex customer programs and escalations.
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 and alignment session to confirm business outcomes, technical scope, success metrics, owners, dependencies, and risks. I would then build a phased execution plan covering architecture validation, onboarding, enablement, governance, go-live criteria, and adoption milestones, with clear escalation paths and regular executive updates.
I would acknowledge the issue quickly, establish an incident lead and communication cadence, and separate immediate mitigation from root-cause investigation. I would coordinate the appropriate Databricks support, engineering, and services resources, provide transparent status updates, and conclude with a corrective-action plan that addresses both the technical issue and prevention measures.
I define value metrics with stakeholders before delivery, such as reduced pipeline runtime, lower infrastructure cost, improved model deployment speed, user growth, or faster time to insight. I map each metric to specific technical deliverables and review progress through an agreed KPI dashboard and governance cadence.
I would assess data volume and velocity, workload patterns, reliability requirements, security and governance, cost controls, user personas, integration dependencies, and operational ownership. I would use these inputs to recommend scalable data ingestion, storage, compute, orchestration, observability, and optimization patterns appropriate to the customer’s maturity and goals.
I prioritize based on business impact, production risk, customer commitments, dependency criticality, and effort. I make the prioritization transparent through a shared roadmap, assign accountable owners, track milestones and blockers consistently, and escalate trade-off decisions early when capacity or timing conflicts arise.
At Databricks, we are on a mission to empower our customers to solve the world’s toughest data problems by utilizing the 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 in your customers. You will also help ensure customer success by increasing focus and technical accountability to our most complex customers who need guidance to accelerate usage on Databricks workloads that they have already selected, helping them maximise the value they get of our platform and the 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 through leading your customers’ stakeholders, building executive relationships, orchestration of other focused/specialized teams within Databricks, and creating and driving plans and strategies for Databricks colleagues to build upon. This is in parallel to being technical, with expectations being that you become 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 with an organisation. 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 prioritised customers
- Lead the post-technical win technical account strategy and execution plan for the majority of Databricks use cases within our most strategic accounts
- Be the accountable technical leader assigned to specific use cases and customer(s) across multiple selling teams and internal stakeholders, creating certainty from uncertainty and driving onboarding, enablement, success, go-live and healthy consumption of the workloads where the customer has made the decision to consume 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, oftentimes services multiple use cases within the largest and most complex organizations
- Leverage both Shared Services, User Education, Onboarding/Technical Services and Support resources, along with escalating to expert level technical experts to build the right tasks that are beyond your scope of activities or expertise
- Create, own and execute a point-of-view as to how key use cases can be accelerated into production, coordinating with Professional Services (PS) resources on the delivery of PS Engagement proposals
- Navigate Databricks Product and Engineering teams for new product Innovations, private previews and upgrade needs
- Develop an execution plan that covers all activities of all customer-facing technical roles and teams to cover the below 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 – KPI reporting on the status of usage and customer health, covering investment status, important risks, product adoption and use case progression – to your Technical GM
What we look for:
- 5+ years of experience where you have been accountable for technical project / program delivery within the domain of Data and AI and where you can contribute to technical debate and design choices with 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 related distributed data systems
- Understanding of how to attribute business value and outcomes to specific project deliverables
- Technical program, or project management including account, stakeholder and resource management accountability
- Experience resolving complex and important escalation with senior customer executives
- Experience conducting open-ended discovery workshops, creating strategic roadmaps, conducting business analysis and managing delivery of complex programmes/projects
- Track record of overachievement against quota, Goals or similar objective targets
- Bachelor’s degree in Computer Science, Information Systems, Engineering, or equivalent experience through work 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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