Data & AI Solutions ArchitectRole Overview
The Data & AI Solutions Architect is a trusted technical advisor and design authority within a Data & AI practice. This role works directly with clients to lead discovery, assessment, and architecture engagements across the full spectrum of modern data and AI solution delivery — from greenfield platform builds to legacy modernisation programmes.
The architect translates business strategy and technical requirements into clear, well-structured architectural designs across conceptual, logical, and detailed levels, grounded in the Microsoft Azure ecosystem.Key Responsibilities
Advisory & Assessment
- Lead or contribute to data and AI advisory engagements, including current-state assessments, maturity evaluations, and technology gap analysis
- Facilitate structured discovery workshops with stakeholders across business, data, and technology functions
- Produce findings and recommendations in the form of assessment reports, roadmaps, and business cases
- Advise on platform strategy decisions, including build vs. buy, cloud-native vs. hybrid, and migration sequencing
Architecture Design
- Develop conceptual architectures to communicate vision and key design decisions to executive and business audiences
- Produce logical architectures defining components, data flows, integration patterns, and system interactions
- Create detailed technical architectures to guide implementation teams, including infrastructure, security, networking, and data design
- Ensure alignment with enterprise standards, governance frameworks, and non-functional requirements such as scalability, resilience, and cost optimisation
Solution Domains
- Design modern data analytics platforms, including data lakehouse, medallion architecture, and real-time streaming solutions
- Architect data modernisation pathways from legacy on-premises platforms (e.g. SQL Server, Teradata, Hadoop) to Azure-native equivalents
- Design AI and machine learning solutions, including predictive analytics, generative AI integrations, and MLOps platforms
- Advise on data governance, data mesh, and data product operating models
Client Engagement
- Build and maintain trusted relationships with client architects, technology leads, and senior stakeholders
- Present architectural proposals and recommendations to both technical and non-technical audiences
- Support pre-sales activities, including solution scoping, estimation, and proposal development
- Contribute to practice development through reusable assets, reference architectures, and thought leadership
Required Skills & Experience
Technical
- Strong hands-on and design experience across the Microsoft Azure Data & AI stack, including:
- Azure Synapse Analytics
- Microsoft Fabric
- Azure Data Factory
- Azure Databricks
- Azure Data Lake Storage
- Azure OpenAI Service
- Azure Machine Learning
- Microsoft Purview
- Proficiency in architectural patterns such as Lambda, Kappa, medallion/lakehouse, and event-driven architectures
- Understanding of data modelling approaches, including dimensional modelling, data vault, and semantic layer design
- Familiarity with DevOps and DataOps practices, including CI/CD pipelines, infrastructure-as-code (Bicep/Terraform), and version control
- Working knowledge of data security, identity, and governance patterns in Azure
Architecture & Consulting
- Proven experience producing architecture artefacts at conceptual, logical, and detailed levels
- Ability to facilitate workshops and drive stakeholder alignment across complex organisations
- Experience conducting technology assessments and developing actionable roadmaps
- Strong documentation skills with the ability to produce clear, professional deliverables
Interpersonal
- Confident presenting and defending architectural decisions to senior audiences
- Strong collaboration skills across multidisciplinary teams
- Ability to manage ambiguity and bring structure to complex, evolving situations
Desirable Experience
- Exposure to non-Microsoft data platforms (e.g. Snowflake, AWS, GCP, Databricks on non-Azure)
- Experience working in Agile delivery environments
- Background in an industry such as financial services, retail, or public sector
- Familiarity with enterprise architecture frameworks such as TOGAF or Zachman
Certifications (Preferred)
- Microsoft Certified: Azure Data Engineer Associate (DP-203)
- Microsoft Certified: Azure Solutions Architect Expert (AZ-305)
- Microsoft Certified: Fabric Analytics Engineer Associate (DP-600)
- Microsoft Certified: Azure AI Engineer Associate (AI-102)
Success Metrics
- Quality and consistency of architecture deliverables
- Client satisfaction and strength of trusted advisor relationships
- Contribution to pre-sales pipeline through technical credibility and proposal quality
- Development of reusable assets and reference architectures