Presales Data & AI Architect - Azure

Presales Data & AI Architect - Azure

Permanent - Fulltime

Homebased - Hybrid working in the UK

(No sponsorship can be offered) - Must be SC Cleared or SC Clearable

As a Presales Data Architect, you would shape, position, and design next-generation data and AI solutions using Azure Synapse, Azure Databricks, Microsoft Fabric, and Azure ML. You’ll be at the forefront of Microsoft’s modern data ecosystem—partnering with enterprise clients, supporting bids and proposals, running discovery workshops, and translating business goals into scalable, commercially viable architectures.

This role combines technical leadership with strategic presales influence: solutioning, estimating, shaping delivery approaches, and guiding customers toward modern cloud, analytics, and AI adoption. You will work closely with technical specialists, industry experts, and executives to help organisations turn complex data challenges into real business outcomes.

Key Responsibilities

Pre-Sales & Solution Strategy

• Lead architecture and design of enterprise Microsoft Azure Data & AI solutions
• Own technical strategy in pre-sales engagements
• Facilitate discovery workshops and client solution envisioning sessions
• Translate business challenges into scalable, secure architecture blueprints
• Act as Technical Design Authority (TDA) across engagements
• Provide effort estimations, risk assessments, and solution roadmaps

What We’re Looking For

• Enterprise-level Azure Data & AI architecture experience
• Proven success in presales and solution shaping roles
• Strong executive communication and stakeholder engagement skills
• Ability to balance hands-on technical depth with strategic advisory
• Experience acting as Technical Design Authority in complex programmes

Technical Expertise

Microsoft Azure Data Ecosystem

• Azure Data Factory (ADF)
• Azure Synapse Analytics
• Microsoft Fabric
• Azure SQL
• Azure Storage
• Power BI
• Azure Service Bus

AI & Advanced Analytics

• Machine Learning architecture design
• Generative AI solution design and deployment
• Azure Cognitive Services
• Responsible AI governance frameworks
• Ethical AI implementation practices