Solutions Architect – Data & AI (Field Engineering)

About the role

As a Solutions Architect in Databricks’ Global Capability Center Field Engineering team, you will work with Fortune‑500 and AI‑forward SaaS customers to design and implement data and AI solutions on the Databricks Data Intelligence Platform.

Key responsibilities

• Act as trusted technical advisor for strategic accounts, influencing architectural decisions across data, AI/ML and platform engineering.
• Partner with sales and product teams to shape customers’ AI strategy, design GenAI and ML architectures, and drive adoption of Databricks solutions.
• Develop and deliver proofs of concept for lakehouse, data engineering, warehousing, and machine‑learning projects, including cloud and third‑party integrations.
• Collaborate with regional field teams and global Solutions Architects to provide consistent guidance across geographies.
• Promote and contribute to Databricks‑inspired open‑source projects such as Spark, Delta Lake, MLflow and Unity Catalog.

Required profile

• 12+ years of experience in data engineering, data science, technical architecture or pre‑sales consulting.
• 8+ years of hands‑on work with Big Data and AI technologies, preferably with Fortune‑500 or global SaaS customers.
• Proven ability to design, whiteboard and build end‑to‑end solutions for enterprise‑scale distributed systems.
• Strong consulting and customer‑facing experience across multiple industries.
• Willingness to travel regionally and occasionally internationally.

Required skills

• Apache Spark™
• Lakehouse architecture (Delta Lake, Unity Catalog)
• Python, SQL, Scala, Java, or R
• Public cloud platforms: AWS, Azure, or GCP
• Data engineering, data warehousing, machine‑learning and GenAI workloads