Senior Solutions Architect (Pre-sales) - Life Sciences

About the role

Databricks is looking for a creative, execution-oriented Senior Solutions Architect to join its Benelux team and drive the technical and consumption strategy for a major life science company. You will work with regional account executives and the global account team on large, complex, multinational accounts, acting as a trusted advisor on enterprise data and AI strategy.

Key responsibilities

• Drive technical and consumption strategy for complex customer engagements, influencing platform adoption and revenue growth.
• Lead complex architecture engagements: multi-workload platforms, enterprise-wide migrations, real-time systems and AI/ML at scale, including GenAI and agentic AI workflows (Agent Bricks, AI Functions, LLMOps).
• Develop and execute competitive strategies against incumbent and emerging platforms.
• Orchestrate cross-functional teams (Delivery and Specialist SAs, Partners, Product) to deliver enterprise-grade solutions.
• Mentor others and coach junior engineers and architects on technical depth, customer engagement and use-case prioritisation.
• Contribute to Field Engineering thought leadership through customer-facing content, workshops and community engagement.

Required profile

• 8+ years in a global, multi-architect account team combining solutions architecture, principal engineering and technical pre-sales leadership.
• Deep expertise in enterprise data architecture: distributed systems at scale, streaming and real-time, lakehouse design patterns, data governance and cloud-native platforms.
• Expert-level knowledge of a data platform (Databricks or a similar modern data and AI platform) with rapid learning ability.
• Executive presence: able to influence Directors, VPs and C-level stakeholders on long-term data and AI strategy, with proven track record of driving consumption growth in large accounts.
• Bachelor's or Master's degree in Computer Science, Engineering or a quantitative discipline (advanced degrees valued).

Required skills

• Hands-on technical background and coding proficiency in Python, SQL and ideally Spark/PySpark; live coding assessment and platform prototype build during interviews.
• Nice to have: Databricks certifications, prior experience at Databricks, Snowflake, AWS, Google, Microsoft or a top data/AI company, published thought leadership, and Life Sciences or GxP pharma experience.