Data & AI Platform Architect (professional Services)

Databricks Databricks · Data AI · Denmark · Professional Services Operations

This role is for a Data & AI Platform Architect within Databricks' Professional Services team. The primary focus is on customer engagements to help them leverage the Databricks platform for big data and AI initiatives. Responsibilities include designing and building reference architectures, productionalizing use cases, and providing technical consulting for data engineering, data science, and cloud projects. The role requires strong experience in data engineering, distributed computing (Spark), cloud ecosystems, and MLOps, with a focus on successful customer adoption and project delivery.

What you'd actually do

  1. You will work on a variety of impactful customer technical projects which may include designing and building reference architectures, creating how-to's and productionalizing customer use cases
  2. Work with engagement managers to scope variety of professional services work with input from the customer
  3. 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
  4. Consult on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks.
  5. Provide an escalated level of support for customer operational issues.

Skills

Required

  • Extensive 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.

Nice to have

  • Databricks Certification

What the JD emphasized

  • customer technical projects
  • productionalizing customer use cases
  • transformational big data projects
  • end-to-end design, build and deployment
  • technical project delivery

Other signals

  • customer-facing
  • professional services
  • Databricks platform
  • big data
  • data engineering
  • data science
  • cloud technology
  • productionalizing use cases
  • transformational big data projects
  • end-to-end design, build and deployment
  • MLOps
  • data architectures
  • technical project delivery