Forward-Deployed Data & AI Architect

Databricks; Greater London; Hybrid; GBP 90,000 - 130,000; Full time

Job summary

Databricks is seeking a Forward Deployed Engineer in London (hybrid) to own architecture and delivery of data and AI solutions for customers. You will lead design decisions, implement end-to-end systems, and collaborate across engineering, product, and customer teams to drive measurable outcomes.

The role requires hands-on engineering skills with Python/Scala/JS, cloud experience, and expertise in Spark. Travel to customer sites is expected up to 20% to ensure successful deployments and adoption.

Qualifications

• Several years of experience in data engineering, data platforms or software engineering.
• Proficiency in Python, Scala or JavaScript/TypeScript.
• Experience with distributed computing using Apache Spark.
• Working knowledge of one or more cloud ecosystems (AWS, Azure, GCP).
• Familiarity with CI/CD for production deployments and ML/AI model deployment.

Responsibilities

• Lead production-grade delivery projects and reference architectures for data and AI solutions.
• Design end-to-end data pipelines, ML/AI integration, and application components for customers.
• Collaborate with engineering, product, and customer teams to align with Databricks best practices.
• Embed with customer teams to understand challenges and deliver measurable impact.
• Provide feedback on product and support issues to improve engagements.

Skills

Data engineering

Data platforms

Analytics

Software engineering

Python

Scala

JavaScript/TypeScript

Cloud (AWS/Azure/GCP)

Apache Spark

Git

Tools

Apache Spark

Git

Job description

Databricks is seeking a Forward Deployed Engineer in London (hybrid) to own architecture and delivery of data and AI solutions for customers. You will lead design decisions, implement end-to-end systems, and collaborate across engineering, product, and customer teams to drive measurable outcomes.

The role requires hands-on engineering skills with Python/Scala/JS, cloud experience, and expertise in Spark. Travel to customer sites is expected up to 20% to ensure successful deployments and adoption.