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Delivery Solutions Architect - Digital Native Business

Join Databricks as a Delivery Solutions Architect to empower customers in solving complex data and AI challenges.

Location
United States
Compensation
$180k–$247.5k/yr
Level
senior
Type
full time

Posted by employer 1 day ago

First seen on Joblaze 1 day ago

Last verified on the company career page 1 day ago

Skills & Technologies

What you'll build

  • Define technical execution strategies
  • Serve as a trusted technical advisor
  • Design scalable Databricks architectures
  • Drive adoption and consumption
  • Mentor peers and contribute technical guidance

Must have

  • 5+ years in solutions architecture
  • Strong coding proficiency in Python, SQL, Scala
  • Deep understanding of distributed data systems
  • Experience designing secure, governed, scalable data solutions
  • Ability to solve ambiguous technical problems
  • Bachelor's degree in Computer Science or equivalent experience

Nice to have

  • Databricks experience or certification
  • Experience with AWS, Azure, or GCP
  • Developing expertise in AI/ML or data engineering
  • Experience creating reusable technical frameworks
  • Experience with production cloud deployments

Practical constraints

  • Travel: Up to 30% as needed

Requirements

Experience
5+ years
Education
Bachelor's degree

Not disclosed in this posting: work arrangement, visa sponsorship.

Joblaze summary

In the role of Delivery Solutions Architect at Databricks, the individual will engage with sales and engineering teams to enhance customer adoption of the Databricks platform through technical guidance and architectural design. Key skills include proficiency in Python, SQL, and a solid understanding of distributed data systems and cloud architectures. This position is ideal for candidates with over five years of experience in solutions architecture or related fields, particularly those who can navigate complex technical discussions with senior stakeholders. The role emphasizes collaboration across teams to drive successful implementation and measurable business outcomes.

Joblaze insights

  • Listed yesterday — first seen on Joblaze September 29, 2026. Last confirmed on Databricks's careers page September 29, 2026.
  • This exact title is also open at 1 other location at Databricks: Remote - California; Remote - Oregon; Remote - Washington.
  • Salary band is in line with the typical range for Data Engineering roles (median ~$180,200).
  • Starts above 32% of 140 comparable senior data engineering roles in United States that list Python we track (median $180,656 across 40 companies). See Python salary trends
  • Python appears in 81.8% of 214 comparable senior data engineering roles in United States; Data Engineering appears in 2.3% of 214 comparable senior data engineering roles in United States.

Quick facts

What's the salary range?
Databricks lists $180,000–$247,500 for this role.
How much experience is required?
At least 5 years of relevant experience for this Delivery Solutions Architect - Digital Native Business role.
What's the tech stack?
Joblaze extracted these technologies from the posting: AI/ML, Cloud, Data Engineering, Python, SQL, Scala.
What seniority level is this role?
Databricks targets senior candidates for this position.
Is this full-time or contract?
Full-time for this Delivery Solutions Architect - Digital Native Business role at Databricks.

From the original posting

At Databricks, we are on a mission to empower our customers to solve the world's toughest data and AI problems by utilizing the Databricks Data Intelligence Platform. As a Delivery Solutions Architect (DSA), you will partner with Sales, Solutions Architecture, and Field Engineering to accelerate adoption and growth of the Databricks platform. You will serve as a trusted technical advisor, helping customers design, implement, scale, and optimize data and AI solutions that deliver measurable business value.

This is a technical and customer-facing role focused on architecture, technical strategy, and customer outcomes. You will influence technical execution across complex use cases, guide architectural decisions, and align Databricks, customer, and partner teams from technical win through production and adoption.

The Impact You Will Have

  • Define and influence technical execution strategies across complex use cases and multiple workstreams within strategic accounts
  • Serve as a trusted technical advisor to customer technical leads and architects, leading architecture discussions and guiding technical decisions
  • Design secure, governed, and scalable Databricks architectures while balancing performance, cost, reliability, and long-term needs
  • Build and demonstrate working solutions, prototypes, and reusable technical assets that accelerate customer outcomes
  • Anticipate platform maturity and scaling needs and establish best practices for security, governance, and operational excellence
  • Drive adoption and consumption by influencing architecture, unblocking delivery, and connecting technical execution to business outcomes
  • Partner across Databricks, customer, and implementation teams to align resources, manage risks, and accelerate delivery
  • Mentor peers and contribute reusable technical guidance, frameworks, and enablement across the organization

What We Look For

  • 5+ years in solutions architecture, solutions engineering, technical consulting, professional services, data engineering, or a related technical role
  • Experience in influencing technical strategy and architecture across complex customer use cases or multiple workstreams
  • Strong coding proficiency in Python, SQL, Scala, or similar languages, with the ability to build, debug, and validate technical solutions
  • Deep understanding of distributed data systems, data engineering, analytics, data warehousing, AI/ML, and modern cloud architectures
  • Experience designing secure, governed, scalable, and production-ready data solutions
  • Ability to solve ambiguous technical problems, evaluate trade-offs, and validate solutions through structured analysis or experimentation
  • Experience leading architecture discussions with technical leads, architects, and senior customer stakeholders
  • Strong understanding of platform operational excellence, including security, governance, performance, reliability, and cost optimization
  • Demonstrated ability to drive customer adoption, consumption, and measurable business outcomes through technical leadership
  • Strong stakeholder management and cross-functional leadership skills, with the ability to align teams without formal authority
  • Bachelor's degree in Computer Science, Engineering, or equivalent experience

Nice to Have

  • Databricks experience or certification
  • Developing expertise in a technical specialization such as AI/ML, data engineering, streaming, data warehousing, governance, or migrations
  • Experience with AWS, Azure, or GCP and production cloud deployments
  • Experience creating reusable technical frameworks, demos, or enablement that scale across teams

Interview Process: Recruiter Screen → Hiring Manager Screen → Design & Architecture → Live Coding → Build, Demo & Pitch → Reference Check

Travel: Up to 30% as 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

Benefits

Standard company text repeated across Databricks's postings is omitted here.

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