Azure Data / AI Architect

Initialize; United Kingdom; Remote; GBP 90,000 - 130,000; Full time

Job summary

Initialize is seeking an Azure Data / AI Architect to lead enterprise-scale data and AI initiatives. This role is remote with hybrid options and occasional client visits, based in the United Kingdom.

You will design modern data platforms using Fabric, Azure Databricks, ADF, ADL, Purview, Synapse Analytics and Power BI, and implement RAG, governance and AI workloads. You will mentor teams and help shape service offerings for delivery excellence.

Qualifications

• Experience designing end-to-end data & AI platforms on Microsoft Azure.
• Proven ability to translate business needs into scalable data architectures.
• Strong background in data integration, warehousing, and modern lakehouse patterns.

Responsibilities

• Architect and oversee enterprise-scale Data & AI solutions on Microsoft Azure.
• Define and evolve Data & AI service offerings, methodologies, accelerators & delivery frameworks.
• Mentor consultants, engineers and architects while promoting knowledge sharing and continuous improvement.
• Ensure security, governance, and compliance across solutions.

Skills

Azure Data & AI Architecture

Enterprise Data Architecture

Data Modeling

Machine Learning & Generative AI

RAG Architectures

Governance & Security

Mentoring/Leadership

Stakeholder Communication

Tools

Microsoft Fabric

Azure Databricks

Azure Data Factory

Azure Data Lake

Power BI

Microsoft Purview

Azure Data Explorer

Synapse Analytics

GitHub

CI/CD Pipelines

Infrastructure as Code

Microsoft Foundry

Copilot Studio

Azure OpenAI

Job description

Azure Data / AI Architect - remote (can be hybrid / client visits when required) - excellent opportunity to join this gold-stamp Azure Partner.

Core Experience

• Microsoft Fabric and/or Azure Databricks

Data Engineering and Analytics (as many of the following as possible)

• Data integration and ETL/ELT design
• Data warehousing methodologies
• Medallion architecture and modern Lakehouse design
• Data modelling and information architecture
• Streaming and near real-time data platforms
• Advanced analytics and reporting solutions
• Machine Learning and Large Language Models

Azure AI (as many of the following as possible)

• Retrieval Augmented Generation (RAG) architectures
• Intelligent document processing and knowledge discovery
• Responsible AI and AI governance principles

Development/DevOps (as many of the following as possible)

• Python and/or C#
• GitHub
• CI/CD pipelines and automation
• Infrastructure as Code principles
• Software engineering and DevOps best practices

Architecture and Governance (as many of the following as possible)

• Security, compliance and governance best practices
• Enterprise architecture and solution governance methodologies

Microsoft Certifications (1 or more...)

Role (Duties include)

• Support the development and growth of the Data and AI practice; Define and evolve Data and AI service offerings, methodologies, accelerators and delivery frameworks; Establish architectural standards, governance principles and quality frameworks to ensure consistent delivery excellence across customer engagements.
• Architect and oversee the delivery of enterprise-scale Data and AI solutions on Microsoft Azure.
• Design modern data platforms using technologies including Microsoft Fabric, Azure Databricks, Azure Data Factory, Azure Data Lake, Microsoft Purview, Azure Data Explorer, Synapse Analytics and Power BI.
• Apply data and semantic modelling best practices including dimensional modelling to deliver consistent, trusted and high-performing analytics solutions.
• Design AI-ready data platforms that support advanced analytics, machine learning and Generative AI workloads.
• Architect solutions leveraging Azure AI Services, Microsoft Foundry, Copilot Studio, Azure OpenAI and Microsoft Fabric capabilities where appropriate.
• Design Retrieval Augmented Generation (RAG) architectures, knowledge discovery solutions and intelligent data-driven applications.
• Promote the adoption of Responsible AI principles, governance frameworks and security controls across customer and internal solutions.
• Act as a trusted technical leader, mentoring consultants, engineers and architects while promoting knowledge sharing and continuous improvement.