Senior Data & AI Solutions Architect — Hybrid London

Fdetimes; Greater London; Hybrid; GBP 120,000 - 180,000; Full time

Job summary

Databricks, London-based, seeks a Senior Forward Deployed Engineer to own architecture and lead design decisions across data engineering, AI, and application development. You will deliver end-to-end solutions for customers, including reference architectures, data ingestion and ML/AI model integration.

The role requires strong cloud, Spark experience, and the ability to work hands-on in a customer-facing setting. Travel up to 20% is expected, with a focus on measurable outcomes and customer value.

Qualifications

• Strong years experience in data engineering, data platforms & analytics, or software engineering.
• Comfortable writing code in Python, Scala, JavaScript/TypeScript and modern frameworks.
• Working knowledge of two or more Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one.
• Deep experience with distributed computing with Apache Spark and Spark runtime internals.
• Familiarity with CI/CD for production deployments.
• Working knowledge of MLOps, ML/AI models and AI APIs.
• Design and deployment of performant end-to-end data architectures and applications.
• Experience with technical project delivery - managing scope, timelines and measurable outcomes.

Responsibilities

• Lead production-grade solution delivery for customer projects with reference architectures and data ingestion.
• Drive end-to-end design, build and deployment of big data and AI applications.
• Guide customers on architecture and design to ensure secure, scalable solutions.
• Collaborate with engineering teams and customer stakeholders to deliver outcomes.

Skills

Python

Scala

JavaScript/TypeScript

Spark

Cloud (AWS/Azure/GCP)

CI/CD

MLOps

Data engineering

Job description

Databricks, London-based, seeks a Senior Forward Deployed Engineer to own architecture and lead design decisions across data engineering, AI, and application development. You will deliver end-to-end solutions for customers, including reference architectures, data ingestion and ML/AI model integration.

The role requires strong cloud, Spark experience, and the ability to work hands-on in a customer-facing setting. Travel up to 20% is expected, with a focus on measurable outcomes and customer value.