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(FEQ327R229)

The Solutions Architect (Lakebase) team executes on Databricks’ strategic Product Operating Model that provides enhanced focus on earlier stage, highly prioritised product lines in order to establish product market fit, and set the course for rapid revenue growth. They are part of a global go-to-market team mandate, though individually will cover a specific, local region.  Clients may span across one or more business units and verticals. By working in partnership with direct account teams, they will jointly engage clients, foster the necessary relationships, position in-depth the specific product line, so as to provide compelling reasons for clients to adopt and grow the usage of the given product.  They understand the appropriate approach, the guardrails, and the steps needed to successfully adopt the product line, as clients deliver on their business objectives.

The Solutions Architect (Lakebase) is paired with an Account Executive aligned to a given product line with specific targets accordingly. Together, they will devise and implement a strategy across their assigned set of accounts, develop presentations, demos and other assets and deliver them such that clients make an informed decision as they decide to adopt the product-line in a meaningful way.

• 6+ years in a customer-facing, pre-sales or consulting role influencing technical executives, driving high-level data strategy and product adoption.
• Proven ability to co-plan large territories with Account Executives and operate in a highly coordinated, cross-functional effort across GTM and R&D teams.
• Experience collaborating with Global System Integrators (GSIs) and third-party consulting organisations to drive customer outcomes.
• Proficient in programming, debugging, and problem-solving using SQL and Python. Also requiring prior experience with Apache Spark or similar analytics engine tooling for large-scale data processing. 
• Hands-on experience building solutions within major public cloud environments (AWS, Azure, or GCP).
• Broad experience (in two or more) and understanding across the fields of data engineering, data warehousing, AI, ML, governance, transactional systems, app development, and streaming.
• Undergraduate degree (or higher) in a technical field such as Computer Science, Applied Mathematics, Engineering or similar.
• A track record of driving complex projects to completion in fast-paced, customer-facing environments.

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