About the role
FEQ128R96 / Stockholm-based
The Role
As a Solutions Architect, you will lead the technical strategy for your customers - owning architecture discussions, driving platform adoption, and serving as a trusted advisor to customer technical leads and architects. You combine deep technical expertise with strategic thinking to position Databricks as the foundation of your customers’ data and AI strategy. You are developing a technical specialisation (archetype) and are recognized within your team for depth in a specific domain.
The Impact You Will Have
- Own the end-to-end technical strategy for your accounts, from initial discovery through production deployment and consumption growth
- Lead complex architecture discussions - designing scalable, production-grade solutions spanning data engineering, ML/AI, and real-time analytics
- Serve as a trusted technical advisor to customer architects, engineering leads, and Directors
- Drive technical wins in competitive scenarios by demonstrating Databricks’ differentiation through custom-built solutions
- Develop and declare an emerging technical specialisation (archetype) - becoming a go-to resource for your team in that domain
- Orchestrate cross-functional resources (DSAs, SSAs, Partners) to deliver comprehensive solutions for complex customer needs
- Influence product direction by providing structured feedback on customer requirements and competitive gaps
What We Look For
- 6+ years customer-facing experience (pre-sales, consulting or advisory) including solutions architecture, data engineering and hands-on technical roles
- Strong coding proficiency and hands-on building skills in Python and SQL - you must demonstrate live coding, debugging, and an AI-first builder mindset.
- Deep expertise in distributed data systems architecture: designing scalable pipelines, streaming architectures, lakehouse patterns, and cloud-native data platforms
- Proficient on the Databricks Platform (or demonstrated ability to achieve proficiency rapidly) with a developing technical specialization in one area (e.g., real-time/streaming, ML/AI, data governance, migrations)
- Proven ability to lead architecture discussions with senior technical stakeholders - whiteboarding, design reviews, and trade-off analysis
- Experience with production deployments on public cloud (AWS, Azure, or GCP), including infrastructure, security, and governance considerations