Technical Program Manager, Professional Services

Responsibilities

• 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
• Design and build reference architectures, create how-to's and productionalize customer use cases
• Work with engagement managers to scope 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
• 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
• Work with Engineering and Databricks Customer Support to provide product and implementation feedback
• Guide customers as they implement transformational big data projects, including end-to-end development and deployment of industry-leading big data and AI applications
• Assure that Databricks best practices are being used within all projects
• Facilitate technical workshops, discovery and design sessions, customer requirements gathering and scoping
• Assist with level of effort estimation and mitigation of risk within customer proposals and statements of work
• Architect, design, develop, deploy, operationalize and document complex customer engagements as the technical lead
• Provide knowledge transfer, enablement and mentoring of other team members, customers and partners

Requirements

• 4+ to 9+ years experience in data engineering, data platforms & analytics (depending on level)
• 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
• Comfort with object-oriented and functional programming in Scala and Python
• Experience in building scalable streaming and batch solutions using cloud-native components
• Strong knowledge of distributed computing with Apache Spark™
• Travel to customers 20% of the time

Nice to Haves

• Databricks Certification