Data & AI Platform Architect

About the Role

As a Data & AI Platform Architect (Internal Title - Resident Solutions Architect) in our Professional Services team, you will collaborate with clients on short to medium‑term engagements addressing their big data challenges using the Databricks platform. You will be responsible for delivering data engineering, data science, and cloud technology projects, which include integrating with client systems, providing training, and performing other technical tasks to maximize customer value from their data.

Resident Solutions Architects are billable and are expected to complete projects according to specifications while providing excellent customer service. You will report to the regional Manager/Lead.

• You will work on a variety of impactful customer technical projects, which may include designing and building reference architectures, creating how‑to guides, and productionalizing customer use cases.
• Work with engagement managers to scope a variety of professional services work with input from the customer.
• Guide strategic customers as they implement transformational big data projects, including 3rd party migrations, and provide 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 that lead to a customer's successful understanding, evaluation, and adoption of Databricks.
• Provide an escalated level of support for customer operational issues.
• You will work with the Databricks technical team, Project Manager, Architect, and Customer team 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.

• Extensive experience in data engineering
  , data platforms
  , and 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.
• Ability to travel to customers 10% of the time.
• [Preferred]
  Databricks Certification but not essential.