Solution Engineer - Data & AI

Overview

As a Solution Engineer – Data & AI, you will help organisations modernise their data estates — from operational databases to enterprise analytics — and unlock business value through AI, Microsoft Fabric, and AI-ready data foundations.

Working alongside account teams, specialists, and partners, you will engage customers throughout their transformation journey, from initial strategy discussions through to technical validation and adoption. You will combine deep technical expertise with industry understanding to design solutions that help customers migrate and modernise mission-critical databases, build enterprise-grade data and analytics architectures, and ground AI on their own data — improving decision-making and creating AI-ready foundations.

You'll work with data leaders, architects, engineers, and business stakeholders to showcase how Microsoft's Data & AI platform — including Azure SQL, Azure Database for PostgreSQL, Azure Cosmos DB, Microsoft Fabric, Power BI, Azure Data Services, and Copilot capabilities — can accelerate innovation and deliver measurable business outcomes.

As a member of the team, you will lead the most complex and strategic customer engagements, influence at architect and executive level, and mentor colleagues — establishing yourself as a recognised technical leader in Data & AI solutions.This role offers the opportunity to work with leading organisations across a broad range of industries, supporting their next-generation data and AI initiatives.

Responsibilities

• Lead strategic customer engagements by helping organizations modernize their data, analytics, and AI platforms to achieve business outcomes.
• Serve as a trusted technical advisor, translating complex business challenges into scalable cloud, data, and AI solutions.
• Design and deliver solution demonstrations, workshops, architecture reviews, and proof-of-concept engagements that support customer decision-making.
• Partner with sales, customer success, engineering, and partner teams to develop technical strategies that accelerate customer transformation and drive business growth.
• Guide customers in adopting modern data platforms, analytics capabilities, governance practices, and AI-enabled experiences.
• Build strong relationships with technical and business stakeholders, influencing architecture and technology decisions throughout the customer lifecycle.
• Contribute to competitive strategies, technical readiness, and solution innovation by sharing market insights, customer feedback, and best practices.
• Mentor peers, contribute to technical communities, and help build a culture of continuous learning, inclusion, and customer obsession.

Qualifications

Required Qualifications:

• Bachelor's degree in Computer Science, Engineering, Information Technology, Data Science, or a related discipline or equivalent practical experience.
• Experience in technical pre-sales, solution architecture, consulting, data engineering, database administration, analytics, or cloud technology roles.
• Experience designing or implementing enterprise-scale data, database, and analytics solutions.
• Experience engaging with both technical and business stakeholders in customer-facing environments.

Required Technical Experience:

• Experience with operational and transactional databases - including SQL Server, Azure SQL (Database & Managed Instance), Azure Database for PostgreSQL, and Cosmos DB - alongside modern analytics platforms.
• Hands-on database migration and modernisation experience, including estate assessment, heterogeneous migration (for example Oracle/PostgreSQL to Azure), and modernisation tooling.
• Hands-on experience building end-to-end analytics solutions in Microsoft Fabric — Lakehouse/Warehouse, Data Factory pipelines, Spark and notebooks, semantic models, Power BI, and Real-Time Intelligence — or comparable modern data platforms such as Databricks.
• Understanding of enterprise-grade non-functional requirements — high availability, disaster recovery, performance tuning, security, resilience, and cost optimisation — across both mission-critical databases and analytics platforms (including Fabric capacity sizing and workload/cost management).
• Familiarity with AI grounding on databases, including vector stores, RAG, and connecting operational data to AI and Copilot experiences.
• Understanding of data engineering, data warehousing, analytics, governance, and modern data architectures across cloud-native and hybrid environments.
• Ability to communicate complex technical concepts clearly to both technical and non-technical audiences.

Solution Engineering IC4 - The typical base pay range for this role across United Kingdom is £ 61,900.00 - £ 105,500.00 per year. Certain roles may be eligible for benefits and other compensation.

Find additional benefits and pay information here:
https://careers.microsoft.com/v2/global/en/corporate-pay/united-kingdom-corporate-pay.html

Solution Engineering IC5 - The typical base pay range for this role across United Kingdom is £ 79,700.00 - £ 133,900.00 per year. Certain roles may be eligible for benefits and other compensation.

Find additional benefits and pay information here:
https://careers.microsoft.com/v2/global/en/corporate-pay/united-kingdom-corporate-pay.html

This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process**.**