Resident Solutions Architect - Public Sector
DatabricksMarylandPosted 4 April 2026
Job Description
CSQ227R175
PLEASE NOTE : Due to federal contract requirements and client site access obligations, U.S. citizenship and eligibility for a U.S. government secret clearance are required to access classified information. The position is based in the Washington, D.C., Maryland, or Virginia metropolitan area and includes periodic on‑site work and client collaboration. Candidates with an active Secret or higher clearance are strongly encouraged to apply.
As a Resident Solutions Architect (RSA) on our Professional Services team, you will work with
customers
on short to medium term customer engagements on their big data challenges using the Databricks platform. You will provide data engineering, data science, and cloud technology projects which require integrating with client systems, training, and other technical tasks to help customers to get most value out of their data. RSAs are billable and know how to complete projects according to specification with excellent customer service. You will report to the regional Manager/Lead.
The impact you will have:
Handle a variety of impactful customer technical projects which may include designing and building reference architectures, creating how-to's and productionalizing customer use cases
Work with engagement managers to scope variety of professional services work with input from the customer
Guide strategic customers as they implement transformational big data projects, 3rd party migrations, including end-to-end design, build and deployment of industry-leading big data and AI applications
Consult on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks.
Provide an escalated level of support for customer operational issues
Collaborate with the Databricks Technical, Project Manager, Architect and Customer teams to ensure the technical components of the engagement are delivered to meet customer's needs
Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues
What we look for:
US Top Secret Clearance Required this position
6+ years experience in data engineering, data platforms analytics
Comfortable writing code in either Python or Scala
Working knowledge of two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one
Deep experience with distributed computing with Apache Spark™ and knowledge of Spark runtime internals
Familiarity with CI/CD for production deployments
Working knowledge of MLOps
Design and deployment of performant end-to-end data architectures
Experience with technical project delivery - managing scope and timelines
Documentation and white-boarding skills
Experience working with clients and managing conflicts
Build skills in technical areas which support the deployment and integration of Databricks-based solutions to complete customer projects
Bachelor's degree in Computer Science, Information Systems, Engineering, or equivalent experience through work experience
Ability to 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 base 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 anticipated 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 he ... (truncated, view full listing at source)
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