Databricks Architect & Delivery Lead — Enterprise Data & AI

Deloitte (UK); Alabama; Hybrid; USD 120,000 - 173,000; Full time

Benefits offered by this job

Hybrid working

London-based role

Job summary

Deloitte is expanding its AI and Data practice in London and seeking an experienced Databricks Architect & Delivery Lead to shape enterprise-scale Data & AI solutions. You will define the technical vision, mobilise multi-disciplinary teams, and ensure secure, scalable delivery aligned with client objectives.

You will lead architecture governance, drive cloud-native strategies, and collaborate with data engineers, analytics specialists, and ML teams to realise measurable business value.

Qualifications

• Proven experience designing enterprise-scale Data & AI architectures on Databricks.
• Strong background delivering large Data & AI transformation programmes.
• Deep knowledge of cloud platforms (Azure/AWS/GCP) and data governance.

Responsibilities

• Lead architecture and technical strategy for large-scale Databricks Data & AI programmes.
• Oversee end-to-end delivery: mobilisation, resourcing, governance, risk and reporting.
• Define end-to-end solution architectures across data engineering, analytics, ML, and Generative AI.
• Establish enterprise data architectures, governance, and cost controls.
• Provide architecture governance and design authority across programmes.
• Collaborate with engineering teams to translate architecture into delivery.

Skills

Databricks architecture

delivery leadership

Data & AI platforms

cloud platforms

governance & security

ML/Ops & LLMOps

stakeholder engagement

architecture governance

Job description

Deloitte is expanding its AI and Data practice in London and seeking an experienced Databricks Architect & Delivery Lead to shape enterprise-scale Data & AI solutions. You will define the technical vision, mobilise multi-disciplinary teams, and ensure secure, scalable delivery aligned with client objectives.

You will lead architecture governance, drive cloud-native strategies, and collaborate with data engineers, analytics specialists, and ML teams to realise measurable business value.