At a glance
- Experience
- 5+ years experience
- Location
- Zürich
About Databricks
- Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.
About the role
- The Delivery Solutions Architect (DSA) partners with Sales, Solutions Architecture, and Field Engineering to accelerate the adoption and growth of the Databricks Data Intelligence Platform.
- This role serves as a trusted technical advisor, guiding customers through the design, implementation, scaling, and optimization of data and AI solutions.
- The position focuses on technical strategy, architecture, and ensuring measurable business outcomes from production through adoption.
Responsibilities
- Define and influence technical execution strategies across complex use cases and multiple workstreams.
- Serve as a trusted technical advisor to customer technical leads and architects.
- Design secure, governed, and scalable Databricks architectures balancing performance, cost, and reliability.
- Build and demonstrate working solutions, prototypes, and reusable technical assets.
- Anticipate platform maturity and scaling needs while establishing best practices for security and governance.
- Drive adoption and consumption by influencing architecture and unblocking delivery.
- Partner across Databricks, customer, and implementation teams to align resources and manage risks.
- Mentor peers and contribute reusable technical guidance and frameworks across the organization.
Requirements
- 5+ years in solutions architecture, solutions engineering, technical consulting, professional services, data engineering, or a related technical role.
- Experience in influencing technical strategy and architecture across complex customer use cases.
- Strong coding proficiency in Python, SQL, Scala, or similar languages.
- Deep understanding of distributed data systems, data engineering, analytics, data warehousing, AI/ML, and modern cloud architectures.
- Experience designing secure, governed, scalable, and production-ready data solutions.
- Ability to solve ambiguous technical problems and evaluate trade-offs.
- Experience leading architecture discussions with technical leads and senior customer stakeholders.
- Strong understanding of platform operational excellence including security, governance, and cost optimization.
- Demonstrated ability to drive customer adoption and measurable business outcomes.
- Bachelor's degree in Computer Science, Engineering, or equivalent experience.
Preferred qualifications
- Databricks experience or certification
- Developing expertise in a technical specialization such as AI/ML, data engineering, streaming, data warehousing, governance, or migrations
- Experience with AWS, Azure, or GCP and production cloud deployments
- Experience creating reusable technical frameworks, demos, or enablement
Benefits
- Comprehensive benefits and perks
Skills
- Python
- SQL
- Scala
- Data Engineering
- Data Warehousing
- AI/ML
- AWS
- Azure
- GCP
- Distributed Data Systems
