Data Platform Solutions Architect (Professional Services) - Emerging Enterprise & DNB

CSQ327R39

We’re hiring for multiple roles within our Professional Services team. Depending on experience and scope, this position may be offered as a Senior Solutions Consultant or a Resident Solutions Architect.

You may know this role as a Big Data Solutions Architect, Analytics Architect, Data Platform Architect, or Technical Consultant. The final title will align to your experience, technical depth, and customer-facing ownership.

As a Data Platform Solutions Architect (Internal Title - Resident Solutions Architect) on our Professional Services team for the Emerging Enterprise & Digital Natives business in EMEA, you will work with clients 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:

Drive high-impact customer projects: Design and build reference architectures, implement production use cases, and create “how-to” guides tailored to the unique needs of fast-moving Emerging Enterprise & Digital Native customers in EMEA.
Collaborate on project scoping: Work closely with Engagement Managers and customers to define project scope, schedules, and deliverables for professional services engagements.
Enable transformational initiatives: Guide strategic customers through their end-to-end big data journeys—migrating from legacy platforms and deploying industry-leading data and AI applications on the Databricks platform.
Consult on architecture & design: Provide thought leadership on solution design and implementation strategies, ensuring customers can successfully evaluate and adopt Databricks.
Offer advanced support: Serve as an escalation point for operational issues, collaborating with Databricks Support and Engineering to resolve challenges quickly.
Align technical delivery: Partner with cross-functional Databricks teams (Technical, PM, Architecture, and Customer Success) to align on milestones, ensuring customer needs and deadlines are met.
Amplify product feedback: Provide implementation insights to Databricks Product and Support teams, guiding rapid improvements in features and troubleshooting for customers.

What we look for:

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

Details

Location

On-site

CSQ327R39

The impact you will have:

Drive high-impact customer projects: Design and build reference architectures, implement production use cases, and create “how-to” guides tailored to the unique needs of fast-moving Emerging Enterprise & Digital Native customers in EMEA.
Collaborate on project scoping: Work closely with Engagement Managers and customers to define project scope, schedules, and deliverables for professional services engagements.
Enable transformational initiatives: Guide strategic customers through their end-to-end big data journeys—migrating from legacy platforms and deploying industry-leading data and AI applications on the Databricks platform.
Consult on architecture & design: Provide thought leadership on solution design and implementation strategies, ensuring customers can successfully evaluate and adopt Databricks.
Offer advanced support: Serve as an escalation point for operational issues, collaborating with Databricks Support and Engineering to resolve challenges quickly.
Align technical delivery: Partner with cross-functional Databricks teams (Technical, PM, Architecture, and Customer Success) to align on milestones, ensuring customer needs and deadlines are met.
Amplify product feedback: Provide implementation insights to Databricks Product and Support teams, guiding rapid improvements in features and troubleshooting for customers.

What we look for:

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