Databricks
Data and AI
ResidentSolutionsArchitect-DigitalNativeBusiness
Neural analysis suggests this role is
optimal for Senior candidates.
“Resident Solutions Architect - Digital Native Business at Databricks. Skills: Data engineering, Apache Spark, Cloud ecosystems, Big data. Integrate with client systems. Provide training”
Industry & Context.
Solve big data problems
Travel 20%
What They're Looking For.
Must Have
9+ years experience in data engineering, 9+ years experience in data platforms, 9+ years experience in analytics, Comfortable writing code in Python, Comfortable writing code in Scala, Working knowledge of AWS, Working knowledge of Azure, Working knowledge of GCP, Deep experience with Apache Spark, Familiarity with CI/CD, Working knowledge of MLOps, Experience with technical project delivery, Experience managing scope, Experience managing timelines, Experience working with clients, Experience managing conflicts
Nice to Have
Databricks Certification
What You'll Do.
Integrate with client systems
Design reference architectures
Build reference architectures
Productionalize customer use cases
Scope professional services work
Guide strategic customers
Implement transformational projects
Migrate 3rd party systems
Design big data applications
Build big data applications
Deploy big data applications
Consult on architecture
Bootstrap customer projects
Implement customer projects
Provide escalated support
Resolve customer issues
Provide product feedback
Provide implementation feedback
Guide rapid resolution
Deploy AI applications
Assure Databricks best practices
Follow quality of service
Facilitate technical workshops
Facilitate discovery sessions
Facilitate design sessions
Gather customer requirements
Estimate level of effort
Develop complex engagements
Deploy complex engagements
Operationalize complex engagements
Document complex engagements
Develop reusable artifacts
Provide consulting experience
Provide client engagement best practices
How You'll Work.
Team & Collaboration
Databricks technical team; Project Manager; Architect; Customer team; Engineering team; Databricks Customer Support; Professional Services team; Extended team
Communication Scope
White-boarding skills
Process & Methodology
Scope management, Timeline management
Full Job Description
CSQ227R258 As a Big Data Solutions Architect (Resident Solutions Architect) in our Professional Services team 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: 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 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. 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. What we look for: 6+ years experience in data engineering, data platforms bootstrap hands-on projects which leads to a customers' successful understanding, evaluation and adoption of Databricks. Provide an escalated level of support for customer
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