CDW
Solution Sales Specialist, Data & AI
Peterborough
Posted about 24 hours ago
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Job Summary
CDW's Solution Sales organisation is in place to collaborate with sales and to be responsible for delivering high value outcomes and experiences to our existing and prospective customers across a variety of Solution Areas.
The Solution Sales organisation is made up predominantly of Sales Specialists, Business Development Managers and various levels of Solution Architects (presales technical resource).
The role of the Solution Sales Specialist – Data & AI is focussed on the following core areas:
- Result driven sales overlay resource focussed on delivering successful financial metrics for the business across the Data & AI portfolio.
- Create and execute on a business plan that delivers against targets and KPI's for data modernisation, data governance and AI adoption.
- Being the sales specialist in the Data & AI domain – data platform, data engineering, data governance and quality, analytics, and applied AI.
- Identify and execute on data-led transformation outcomes with CDW's strategic UK customers, spanning private sector, public sector and regulated industries.
The primary purpose of this role is to add significant value to our customers by improving and preparing their data estate – its quality, structure, governance and accessibility – so that they can enrich and unlock the full value of AI. The role holder leads the sales engagement from start to finish, working proactively with aligned account owners, and is expected to lead the conversation on why AI outcomes depend on data readiness.
The role is to promote and sell the complete CDW portfolio of Data & AI solutions and supporting professional & managed services to our customers, to achieve personal targets that contribute to the overall team target and CDW strategy.
The available portfolio today is extensive but summarised to:
- Data readiness and AI-preparation assessments – data discovery, classification, quality profiling, lineage and 'AI-readiness' health checks that establish the baseline for AI adoption.
- Modern data platform – Microsoft Fabric, Azure Synapse/Databricks, data lakehouse and warehouse design, migration and modernisation from legacy platforms.
- Data engineering and integration – ingestion pipelines, ETL/ELT modernisation, master data management, unstructured content preparation (SharePoint, file shares, Teams) for retrieval-augmented AI.
- Data governance, quality and security – Microsoft Purview, cataloguing, sensitivity labelling, information lifecycle, oversharing remediation and access hygiene ahead of Copilot deployment.
- Analytics and insight – Power BI, semantic models, self-service analytics enablement and reporting rationalisation.
- Applied AI – Microsoft 365 Copilot, Copilot Studio and agents, Azure AI/OpenAI services, machine learning and use-case discovery, pilot and scale programmes.
- AI governance and responsible AI – policy, guardrails, risk, and alignment to UK regulatory expectations (UK GDPR, the EU AI Act where in scope, and sector regulators such as the FCA and NHS/DSPT requirements).
- Supporting professional and managed services – advisory, delivery, adoption and change management, and ongoing managed data and AI operations.
Opportunities are very often multi-stream and the role holder should be able to sell across multiple technologies, joining Data & AI to Hybrid Platforms, Modern Workspace and Security propositions.
Success Measures
BAU Measures
- Revenue and GP generation – Achieving and exceeding personal and team financial targets across Data & AI product, services and annuity revenue.
- Pipeline development – Building and maintaining a robust, qualified Data & AI pipeline, with a healthy mix of data foundation/readiness engagements and downstream AI opportunities.
- Sales cycle execution – Successfully running structured sales cycles from initiation to closure, including assessment-led 'land and expand' motions that begin with data readiness and grow into platform and AI programmes.
- Cross-team collaboration – Effective teamwork with Sales, Solution Architects, Data & AI presales, delivery practices and Business Development Managers to drive business goals.
- Partner engagement – Building and leveraging relationships with Microsoft and other strategic Data & AI vendors to generate co-sell pipeline and access funding programmes.
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Long-term Strategic Change Measures
- Thought leadership – Positioning CDW as the trusted advisor on data readiness for AI through industry insights, customer workshops, executive briefings and events.
- Customer solution adoption – Driving adoption beyond initial sale, ensuring customers move from data preparation into measurable AI value realisation and long-term consumption growth.
- Innovation and adaptability – Staying ahead of a fast-moving Data & AI market, evolving the sales approach and incorporating new capabilities into the sales strategy.
- Proposition development – Contributing customer-informed feedback that shapes CDW's UK Data & AI propositions, assessment offerings and repeatable service packages.
Role-Specific Performance Measures
- Proposal success rate – The percentage of proposals and pitches that lead to successful engagements.
- Data readiness conversion – The percentage of data assessment or readiness engagements that convert into follow-on platform, governance or AI programmes.
- Objection handling and negotiation effectiveness – Measuring how well objections are managed and deals are closed, including commercial models for consumption-based services.
- Sales conversion ratio – Tracking the percentage of qualified leads that convert into successful sales.
- Customer value evidence – Demonstrable, referenceable customer outcomes attributable to improved data quality and governance.
What you will do
- Engaging proactively with existing and prospective customers to understand business challenges and position tailored Data & AI solutions, targeting strategic decision makers (CDO, CIO, CTO, Head of Data, Head of Transformation, CISO) and profiling potential new customers.
- Qualifying and leading the initial business discussions with customers, establishing where their data estate is today and what must change before AI can deliver value.
- Leading the 'data readiness for AI' conversation – articulating why data quality, structure, governance, permissions hygiene and accessibility are prerequisites to successful AI adoption, and converting that into a practical, staged commercial roadmap.
- Scoping and selling data discovery, profiling and AI-readiness assessments as the entry point to broader transformation, then driving the follow-on programme.
- Preparing and presenting compelling proposals, business cases and pitches to customers, both owning and contributing to opportunities, including ROI and value cases for data modernisation and AI adoption.
- Objection handling, negotiating and ultimately closing the sale.
- Achieve and exceed sales targets while maintaining high levels of customer satisfaction as the owner of commercial deals.
- Be the subject matter expert/specialist for Data & AI – data platform, data engineering, data governance and quality, analytics and applied AI – in order to drive pipeline and lead the sale individually.
- Establish new relationships within CDW and externally within the client/prospect base to drive performance goals.
- Build and maintain strong relationships with Microsoft and other Data & AI vendors and their UK field teams, driving co-sell, partner-funded assessments and joint pipeline generation.
- Work in close partnership with the internal CDW Sales and Specialist teams to identify new opportunities whilst driving proactive development of converged pipe/funnel, particularly where Modern Workspace (Copilot), Security (Purview, data protection) and Hybrid Platforms opportunities intersect with Data & AI.
- Build strong relationships with the Account Management team who own the customer relationship and proactively work with them, seeking opportunities and engaging additional CDW personnel as needed.
- Identify client needs and propose end-to-end solutions that enhance efficiency, scalability and data trust – from ingestion and quality through to governed AI consumption.
- Ensure proposed solutions reflect UK data protection, sovereignty, residency and sector regulatory requirements, working with Security and Legal colleagues where required.
- Supporting bid teams with subject matter expertise, including public sector frameworks and formal tender responses.
- Opportunity ownership including CRM hygiene and accurate forecasting.
- Keep up to date with knowledge and stay updated on industry trends and emerging technologies, maintaining relevant vendor certifications and accreditations in the Data & AI space.
- Contribute to customer education through workshops, envisioning sessions, webinars and events that build demand for data readiness and AI.
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What we expect of you
- Demonstrable knowledge of the Data & AI landscape – modern data platforms (Microsoft Fabric, Azure Synapse, Databricks, data lakehouse/warehouse), data engineering and integration, and analytics (Power BI).
- Knowledge of data governance, data quality and data management disciplines – cataloguing, lineage, master data, classification, sensitivity labelling and information lifecycle (e.g. Microsoft Purview).
- Understanding of what makes a data estate 'AI-ready' – content quality and structure, metadata, permissions and oversharing risk, unstructured data preparation, and retrieval patterns that underpin Copilot and agentic AI.
- Knowledge of applied AI and its commercial application – Microsoft 365 Copilot, Copilot Studio/agents, Azure AI and OpenAI services, and machine learning use cases.
- Working knowledge of the UK regulatory and compliance environment as it applies to data and AI – UK GDPR and the Data (Use and Access) Act, data residency and sovereignty, the ICO's expectations, sector requirements (financial services/FCA, NHS DSPT and healthcare, public sector), and emerging AI governance standards such as ISO/IEC 42001 and the EU AI Act where UK customers are in scope.
- Knowledge of UK public sector routes to market and procurement frameworks (e.g. G-Cloud, Crown Commercial Service agreements).
- Knowledge of a structured sales process.
- Knowledge of different customer personas, including data, technology, security, risk and line-of-business stakeholders.
- Knowledge of consumption and annuity commercial models (Azure consumption, licensing, managed services) and how to build a compelling multi-year value case.
Required experience:
- Demonstrable experience in delivering successful sales growth performance – running a structured sales cycle from start to finish, ideally within data, analytics, cloud or AI solutions and services.
- Experience selling data and/or AI services in the UK market, including assessment-led engagements that grow into larger transformation programmes.
- Experience of working in sales environments and contributing to sales proposals, bid responses and customer meetings.
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