Data Engineering Architect

Reed.co.uk
London, United Kingdom
2 months ago
Applications closed

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Data & AI Architect - Hybrid (London) - Azure - Fabric - Modern Data Architectureup to £110,000 If you're looking for a senior role where you can influence how Data & AI is shaped and delivered within a fast-growing Microsoft partner, this is an opportunity that truly stands out. The organisation is investing heavily in modern cloud, analytics and AI and they're building a team where experienced voices can make a real difference.
With modern tools, varied client work and a people-focused approach, this is a place where a strong Data & AI leader can have a meaningful impact while helping scale a rapidly expanding data function.
Running gap-analysis sessions, contributing to the sales cycle and helping strengthen the organisation's data-led presales capability.
Microsoft Data & AI Ecosystem

The full modern Microsoft data stack: Fabric, Azure Data Factory, Synapse, Azure SQL, Azure Storage and Power BI.
Advanced AI technologies including machine learning, generative AI, cognitive services, and responsible AI frameworks.
A heavy focus on Power Platform and Dataverse, as all customer data interacts with these technologies.
Designing scalable enterprise architectures, not ad-hoc integrations.
Modern Data Architecture

Lakehouse, data mesh, ELT/ETL patterns, MDM and dimensional modelling.
Steering the "doers" in the team-architecting the solution, not building it yourself.
Mentoring and guiding a growing data team.
Helping establish a maturing Data & AI division set for significant expansion over the coming years.
Creating reusable accelerators and assets alongside the Product team.
Health & wellness benefits covering medical, dental and eye care, plus health cashback.
~ Car allowance inclusive of salary
~ Cycle to Work scheme.
~ 24-hour Employee Assistance Programme.
~ Gym and retail discounts.
~ Expected to attend London-based client sessions once per week.

Strong expertise across Azure data and AI services, including Fabric and ADF.
Demonstrable experience architecting complex, enterprise data and AI platforms.
Knowledge of Dynamics 365, DevOps pipelines and Agile delivery.
Experience with ML, generative AI and cognitive services.
Expertise in lakehouse, data mesh, ELT/ETL, MDM and modelling techniques.
Willingness to travel for client sessions (primarily London).
If you're passionate about leading modern Data & AI architecture, enjoy shaping presales strategy, and want to play a key role in scaling a fast-growing division, this is an opportunity you won't want to miss.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Where to Advertise Machine Learning Jobs in the UK (2026 Guide)

Where to advertise machine learning jobs UK in 2026: the specialist boards and communities that reach ML, MLOps and deep learning engineering talent. The candidate pool is small, highly specialised and in demand across AI labs, financial services, healthcare, autonomous systems and consumer technology simultaneously. Machine learning engineers and researchers move between roles through professional networks, conference communities and specialist platforms — not general job boards where ML roles compete with unrelated software engineering positions for the same audience. This guide, published by MachineLearningJobs.co.uk, covers where to advertise machine learning roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about hiring across different role types.

Machine Learning Jobs UK 2026: What to Expect Over the Next 3 Years

Machine Learning Jobs UK 2026: roles, salaries and the MLOps, LLM and generative AI hiring trends shaping UK ML careers over the next three years. Machine learning has undergone a transformation that few technology disciplines can match. In the space of three years it has moved from a specialism sitting at the edges of most organisations' technology strategies to a capability that sits at the centre of them. The tools have changed, the expectations have shifted, and the range of industries treating machine learning as a core business function — rather than an experimental one — has expanded dramatically. For job seekers, this creates both opportunity and complexity in roughly equal measure. The machine learning jobs market of 2026 is significantly larger than it was three years ago, but it is also significantly more demanding. Employers have developed more sophisticated expectations, the technical bar for specialist roles has risen, and the landscape of tools, frameworks, and architectural patterns that practitioners are expected to know has broadened considerably. The candidates who will thrive over the next three years are those who understand where the discipline is heading — which specialisms are attracting the most investment, which technologies are reshaping what machine learning engineers and researchers are expected to build, and how the definition of a machine learning career is evolving beyond the model-building core toward a much wider range of roles across the full ML lifecycle. This article breaks down what the UK machine learning jobs market is likely to look like through to 2028 — covering the titles emerging right now, the technologies driving employer demand, the skills that will matter most, and how to position your career ahead of the curve.