Delivery Solutions Architect
Databricks14 hours ago
Munich, GermanySenior
Responsibilities
- Define technical execution strategies across complex customer use cases and multiple workstreams.
- Advise customer technical leads and architects, lead architecture discussions, and guide technical decisions.
- Design secure, governed, scalable, production-ready Databricks architectures while balancing performance, cost, reliability, and long-term needs.
- Build and demonstrate working solutions, prototypes, and reusable technical assets.
- Establish best practices for security, governance, platform maturity, scaling, and operational excellence.
- Drive customer adoption, platform consumption, and measurable business outcomes through technical leadership.
- Align Databricks, customer, partner, and implementation teams; manage risks and accelerate delivery.
- Mentor peers and contribute reusable technical guidance, frameworks, demos, and enablement.
Requirements
- 5+ years of experience in solutions architecture, solutions engineering, technical consulting, professional services, data engineering, or a related technical role.
- Experience influencing technical strategy and architecture across complex customer use cases or multiple workstreams.
- Strong coding proficiency in Python, SQL, Scala, or similar languages, with the ability to build, debug, and validate technical solutions.
- 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, evaluate trade-offs, and validate solutions through structured analysis or experimentation.
- Experience leading architecture discussions with technical leads, architects, and senior customer stakeholders.
- Understanding of security, governance, performance, reliability, cost optimization, and platform operational excellence.
- Demonstrated ability to drive customer adoption, consumption, and measurable business outcomes through technical leadership.
- Strong stakeholder management and cross-functional leadership skills, including the ability to align teams without formal authority.
- Bachelor's degree in Computer Science, Engineering, or equivalent experience.
- Databricks experience or certification is preferred.
- Expertise in a technical specialization such as AI/ML, data engineering, streaming, data warehousing, governance, or migrations is preferred.
- Experience with AWS, Azure, or GCP and production cloud deployments is preferred.
- Experience creating reusable technical frameworks, demos, or enablement that scale across teams is preferred.
Benefits
- Databricks offers comprehensive benefits and perks, with specific details varying by region.
- The role requires up to 30% travel as needed.
Tech Stack
Categories
Solutions Engineering
About Databricks
Databricks builds a cloud-based data and AI platform centered on the lakehouse architecture, combining data engineering, analytics, and machine learning with Apache Spark, Delta Lake, and MLflow. It sells subscriptions and cloud services to enterprises that need to unify data pipelines and develop large-scale AI and analytics. Founded in 2013 by the creators of Apache Spark and headquartered in San Francisco, the company is privately held and serves organizations across many industries.