Customer-Facing Data & AI Solutions Engineer

Databricks; San Francisco (CA); On-site; USD 182,000 - 250,000; Full time

Job summary

Databricks is looking for a Forward Deployed Engineer to partner with customers to build and productionize data & AI solutions on the Databricks platform. You will own the architecture, lead design decisions, and deliver end-to-end systems spanning data engineering, AI, and application development.

You will work cross-functionally with engineering, product, and customer teams to ship production-grade references, accelerators, and scalable data architectures with measurable business impact.

Qualifications

• 6+ years in data engineering, analytics, or software engineering.
• Proficient in Python, Scala, or JavaScript/TypeScript.
• Experience with two or more Cloud ecosystems (AWS/Azure/GCP).
• Deep experience with distributed computing using Spark.
• CI/CD for production deployments; ML/AI model knowledge.
• Experience with enterprise clients and project delivery.

Responsibilities

• Lead production-grade customer projects with reference architectures and data ingestion.
• Design and build end-to-end data/AI applications for customers.
• Collaborate with engagements managers to scope delivery work.
• Guide architecture decisions to secure and scalable solutions.
• Embed with customer teams and communicate with stakeholders.
• Contribute accelerators and best practices to scale impact.

Skills

Python

Scala

JavaScript/TypeScript

Cloud: AWS/Azure/GCP

Apache Spark

CI/CD

MLOps

Data engineering

Customer-facing

Production systems

Job description

Databricks is looking for a Forward Deployed Engineer to partner with customers to build and productionize data & AI solutions on the Databricks platform. You will own the architecture, lead design decisions, and deliver end-to-end systems spanning data engineering, AI, and application development.

You will work cross-functionally with engineering, product, and customer teams to ship production-grade references, accelerators, and scalable data architectures with measurable business impact.