Databricks

Technology

SeniorSolutionsArchitect-Lakebase

€115–165k ~AI est. Paris, France
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“Senior Solutions Architect - Lakebase at Databricks. Engage clients. Foster relationships”

Industry & Context.

Technology
Problems you'll solve

Problem-solving

What They're Looking For.

Must Have

10+ years transactional database expertise, 6+ years customer-facing pre-sales or consulting role, Proficient in SQL and Python, Hands-on experience in major public cloud environments, Broad experience in data engineering, data warehousing, AI, ML, governance, transactional systems, app development, and streaming

Nice to Have

Credibility in influencing OLTP products, Experience architecting solutions integrating transactional data systems within Big Data, Lakehouse, and AI ecosystems, Infrastructure, platform and administration expertise around disaster recovery, high availability, backup and recovery, scale-out methods, identity and security management, migrations, Experience collaborating with Global System Integrators (GSIs) and third-party consulting organizations, Undergraduate degree (or higher) in a technical field

What You'll Do.

Position product line

Provide compelling reasons for adoption

Understand approach and guardrails

Deliver on business objectives

Devise and implement strategy

Develop presentations and demos

Make informed decisions

Design and execute engagement strategies

Serve as expert Solutions Architect

Build technical credibility

Drive product adoption and vision

Enable clients at scale

Develop customer-facing collateral

Increase technical knowledge

Translate field-derived insights

Make strategic recommendations

Handle complex technical challenges

Act as tier-3 escalation point

Ensure customer success

How You'll Work.

Team & Collaboration

Partnership with direct account teams; Co-plan large territories with Account Executives; Coordinated, cross-functional effort across GTM and R&D teams; Collaborate with Global System Integrators; Collaborate with third-party consulting organizations; Collaborate with GTM leadership; Collaborate with account teams; Collaborate with Product and Engineering teams

Communication Scope

Thought leadership

Full Job Description

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. The Lakebase product-line requires the following core technical competencies: 10+ years of transactional database (OLTP) expertise across engineering, product development, administration, and pre-sales, with a proven track record of designing and delivering client-facing solutions. Credibility in influencing OLTP products with the market insight needed to shape and prioritise roadmap capabilities. Experience architecting solutions that integrate transactional data systems within broader Big Data, Lakehouse, and AI ecosystems. Infrastructure, platform and administration expertise around disaster recovery, high availability, backup and recovery, scale-out methods, identity and security management, migrations (vendor-to-

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