Senior Solution Architect, Data & AI

CDW; Greater London; On-site; GBP 85,000 - 120,000; Full time

Job summary

CDW UK is looking for a Senior Solutions Architect, Data to lead the technical response on data platform opportunities within our Data & AI practice. Working with the wider solution sales organisation, you design modern data platforms—unified or federated—that collect, store, integrate, process, govern and analyse data to enable data-driven decisions and AI.

Modernisation is central: help customers move from legacy warehouses and fragmented estates toward lakehouse, warehouse, and federated

Responsibilities

• Enterprise Data Strategy - Advise customers on data strategy and target-state architecture, linking business priorities to a practical data platform roadmap that supports analytics, operational decisions and AI.
• Data Estate Modernisation - Lead the technical case for modernising legacy data warehouses, databases and fragmented data estates. Assess the current state, define migration approaches and phased roadmaps, and identify risks, dependencies and quick wins.
• Data Architecture & Modelling - Design end-to-end data platform architectures, including lakehouse, warehouse, federated and data-product approaches. Apply appropriate modelling patterns such as medallion, dimensional and domain-oriented designs.
• Data Integration & Engineering - Design ingestion and integration patterns across batch, streaming and change data capture (CDC). Define ETL/ELT, transformation and orchestration approaches suited to the customer's scale, skills and operating model.
• Data Storage & Management - Design the logical storage layer, including open table formats, database selection, partitioning, retention and lifecycle management. Work with Hybrid Platforms architects, who own physical storage and infrastructure.
• Data Governance, Discovery & Quality - Design governance into every solution, covering cataloguing, lineage, ownership, business classification, data quality and access policy. Work with Security architects, who own data protection and data loss prevention.
• Semantic Layer & Analytics - Design the semantic and business-model layer that provides consistent, trusted definitions for BI, self-service analytics and AI. Guide analytics and visualisation choices without building dashboards or reports.
• AI-Ready Data - Make sure data platforms provide the quality, context, access and governance that AI and machine learning need. Work with the Principal AI Architect on AI use cases that depend on the data foundation.
• Security, Observability & FinOps by Design - Build security, privacy, monitoring, reliability and cost management into every layer of the architecture. Give customers a clear view of consumption-based platform

Job description

At CDW, we make it happen, together. Trust, connection, and commitment are at the heart of how we work together to deliver for our customers. It’s why we’re coworkers, not just employees. Coworkers who genuinely believe in supporting our customers and one another. We collectively forge our path forward with a level of commitment that speaks to who we are and where we’re headed. We’re proud to share our story and Make Amazing Happen at CDW.

Job Summary

The Senior Solutions Architect, Data leads the technical response on data platform opportunities within CDW UK's Data & AI practice. Working alongside the wider solution sales organisation they design modern data platforms, whether unified or federated, that let customers collect, store, integrate, process, govern and analyse their data. The result is a trusted, secure, scalable, and cost-efficient foundation for data-driven decisions and AI. Modernisation is at the heart of the role: helping customers move away from legacy data warehouses, databases and fragmented data estates towards modern lakehouse, warehouse and federated designs on platforms such as Databricks, Snowflake, Microsoft Fabric and Starburst.

Role

In a pre-sales capacity, there is a demand for both technical and commercial awareness coupled with an ability to communicate with a wide range of customer stakeholders.. The role qualifies the technical requirement on opportunities, leads discovery with business, data and IT stakeholders, and turns customer goals into technical valid, commercially credible designs covering:

• Data Ingestion and Integration
• Storage and management
• Processing and Transformation
• Design of the Semantic Layer
• Data Sharing
• Delivery of AI-ready data

Governance, security, observability and cost are designed in at every stage.

They work closely with Solution Sales Specialists, Partners and their fellow architects in associated domain specialistations. Physical storage, Infrastructure and Cloud platforms are handed to Hybrid Platforms Practice, with Data Protection and Governance coming from our Security Practice.

The role also has input into the Data Platforms go-to-market by creating reusable reference architectures, modernisation assessments, demonstrations and packaged offerings. The candidate also supports sales enablement and the development of colleagues across the practice

What You Will Do

• Enterprise Data Strategy - Advise customers on data strategy and target-state architecture, linking business priorities to a practical data platform roadmap that supports analytics, operational decisions and AI.
• Data Estate Modernisation - Lead the technical case for modernising legacy data warehouses, databases and fragmented data estates. Assess the current state, define migration approaches and phased roadmaps, and identify risks, dependencies and quick wins.
• Data Architecture & Modelling - Design end-to-end data platform architectures, including lakehouse, warehouse, federated and data-product approaches. Apply appropriate modelling patterns such as medallion, dimensional and domain-oriented designs.
• Data Integration & Engineering - Design ingestion and integration patterns across batch, streaming and change data capture (CDC). Define ETL/ELT, transformation and orchestration approaches suited to the customer's scale, skills and operating model.
• Data Storage & Management - Design the logical storage layer, including open table formats, database selection, partitioning, retention and lifecycle management. Work with Hybrid Platforms architects, who own physical storage and infrastructure.
• Data Governance, Discovery & Quality - Design governance into every solution, covering cataloguing, lineage, ownership, business classification, data quality and access policy. Work with Security architects, who own data protection and data loss prevention.
• Semantic Layer & Analytics - Design the semantic and business-model layer that provides consistent, trusted definitions for BI, self-service analytics and AI. Guide analytics and visualisation choices without building dashboards or reports.
• AI-Ready Data - Make sure data platforms provide the quality, context, access and governance that AI and machine learning need. Work with the Principal AI Architect on AI use cases that depend on the data foundation.
• Security, Observability & FinOps by Design - Build security, privacy, monitoring, reliability and cost management into every layer of the architecture. Give customers a clear view of consumption-based platform