Senior Solutions Architect

About the role

You will own the technical validation and architectural articulation of the Databricks Lakehouse Platform for strategic UK and European customers within your designated territory. You will translate complex business requirements into compelling, end-to-end data and AI solution designs that leverage the full breadth of the Databricks platform. This role requires you to act as a trusted advisor, challenging current assumptions and guiding executive and technical stakeholders toward optimal outcomes aligned with Databricks vision. You will leverage your deep expertise in data science, machine learning, and generative AI to demonstrate how the Lakehouse accelerates innovation and delivers measurable business value. You will coach and elevate junior team members, fostering a collaborative environment where solution architecture is rigorously debated and continuously refined. Your work will directly influence the adoption of Databricks by driving technical community engagement and shaping the future of data and AI within key enterprise accounts. You will be a visible champion of innovation, ensuring that every interaction reinforces Databricks as the definitive platform for data-driven transformation.

Key facts

What you'll do

Architect and communicate sophisticated end-to-end data and AI solution architectures that address specific customer business problems using the Databricks Lakehouse Platform.

Translate ambiguous customer requirements into clearly defined use cases, success metrics, and technical scopes that guide the sales and delivery teams.

Lead complex, cross-functional discovery sessions with C-level and technical stakeholders to uncover latent needs and validate solution hypotheses.

Design and deliver multi-phase proofs-of-concept that de-risk technical assumptions and demonstrate tangible value before full-scale implementation.

Champion the Databricks platform by articulating its strategic advantages against alternative cloud and on-premise architectures to executive audiences.

Collaborate closely with Account Executives and Customer Success teams to develop account-specific engagement strategies that align with commercial objectives.

Coach Solutions Architects and technical teams on best practices for use case prioritization, data architecture, and fostering technical champions within customer organizations.

Influence stakeholders across the broader cloud ecosystem and third-party application integrations, ensuring seamless alignment with Databricks solution strategy.

Contribute to the development of customer-facing collateral, including workshops, seminars, and thought leadership content that reinforces Databricks technical authority.

Continuously expand your expertise across one of four professional tracks, including technical specialization, industry vertical thought leadership, strategic customer vision, and people management.

Maintain a deep, current understanding of the data and AI landscape, including open-source frameworks and commercial ISV tools such as Dataiku, Domino, and DataRobot.

Act as a hands-on technical advisor capable of diving into detailed architecture discussions with engineers while simultaneously communicating high-level value to executives.

Build and maintain strong, trust-based relationships with key influencers and decision-makers across the customer organization.

Drive the adoption of Databricks by demonstrating how the Lakehouse platform solves complex data challenges and accelerates time-to-value for data initiatives.

Requirements

Hands-on experience in technical pre-sales or consultancy, with a strong background in Data Science, traditional Machine Learning, Deep Learning, Artificial Intelligence, or Generative AI.

Demonstrated ability to architect end-to-end Data and AI solutions, with specific expertise in modern Generative AI concepts such as fine-tuning, RAG, and MLOps for LLMs, using either open source and/or ISV tools such as Dataiku, Domino, DataRobot, and similar platforms.

Strong proficiency in at least one core programming language, such as Python or SQL, a willingness to learn or existing knowledge of Apache Spark is essential.

Proficiency with big data analytics technologies and major public cloud platforms, including Amazon Web Services, Microsoft Azure, or Google Cloud Platform.

Hands-on expertise in designing and delivering complex proofs-of-concept that validate technical feasibility and business value in enterprise environments.

A proven track record of engaging with customers in a technical sales capacity, capable of challenging assumptions and guiding discussions toward clear, actionable outcomes.

Exceptional ability to communicate both technical depth and business value to diverse audiences, ranging from engineers and data scientists to executive decision-makers.

A customer-centric mindset with a passion for building strong internal and external partnerships, and a commitment to fostering long-term client relationships.

The ability to operate effectively in a matrixed environment, managing multiple priorities and stakeholders while maintaining a high degree of professionalism.

Strong analytical and problem-solving skills, with the capacity to synthesize complex information into clear, structured solution narratives.