Data & AI Platform Architect – Professional Services

Databricks

Data & AI Platform Architect engaging with clients on their big data challenges using the Databricks platform. Working collaboratively to deploy data engineering, data science, and cloud technology projects.

Posted 4/27/2026full-timeRemote • 🇩🇰 DenmarkMid-LevelSeniorWebsite

Tech Stack

Tools & technologies

ApacheAWSAzureBootstrapCloudGoogle Cloud PlatformPythonScalaSpark

About the role

Key responsibilities & impact

Work with clients on short to medium-term customer engagements on their big data challenges using the Databricks platform
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
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
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.
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.

Requirements

What you’ll need

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.
Build skills in technical areas which support the deployment and integration of Databricks-based solutions to complete customer projects.
Travel to customers 10% of the time
[Preferred] Databricks Certification but not essential.

Benefits

Comp & perks

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Hard Skills & Tools

data engineeringdata platformsanalyticsPythonScalaAWSAzureGCPApache SparkMLOps

Soft Skills

client managementconflict managementdocumentationwhite-boardingproject deliveryscope managementtimeline managementcommunicationtrainingsupport

Certifications

Databricks Certification