Deployment Strategist
Databricks is a data and AI platform that lets organizations build analytics, AI agents, and applications on a unified, governed lakehouse.
Funding history
Investors
About Databricks
Data engineers, analysts, and AI teams use Databricks to process large datasets, build reliable pipelines, and train models on a single governed platform. Users can run SQL analytics, serve ML predictions in real time, and deploy AI agents grounded in enterprise data. Its open lakehouse architecture provides consistent security and governance across analytical and operational workloads.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will act as a product manager for the field, bridging a customer's major business problem and Databricks' technical solution. You will perform deep discovery, scope value, define the pilot MVP, write the PRD, lead technical design reviews, drive the FDE build team in an agile process, own launch and production readiness, and identify the next engagement.
Requirements
- Strong executive presence and communication skills
- Ability to define what to build and why, write product requirements and manage agile projects
- Understanding of modern data and AI architectures including cloud, pipelines, APIs, security, ML and generative AI
- Proficiency in at least one language such as Python, Java, or SQL
- Typically 7+ years delivering complex customer-facing data, analytics, AI or software engagements
- Willingness to work onsite with customers 25-50% of the time
Responsibilities
- Partner with Sales to perform discovery, map the customer's organization, quantify business value and define the pilot
- Author the PRD, prioritize the engineering backlog, manage scope and act as hands-on QA tester
- Translate business requirements into data, integration, security and operational requirements
- Drive the FDE build team through an agile delivery process and manage stakeholders
- Lead technical discovery and design reviews and identify technical risks early
- Own the Day 0 launch and drive solution to full adoption
- Own production readiness across data quality, testing, security, performance and operations
- Scope ongoing maintenance plan and create customer documentation and training
- Identify the next high-value FDE engagement
- Codify reusable solution patterns and bring field insights back to Product and Engineering