Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Manager, Delivery Solutions Architects

Databricks
London
1 year ago
Applications closed

Related Jobs

View all jobs

Manager (Quantexa) Snr Data Engineer

Data Science Manager - Marketing & Customer Generative AI Enterprise Architect

Senior Data Analyst - Customer and Product

Principal Data Engineer

Full Stack Data Engineer

Data Analyst - Integrations

FEQ225R150

Build and lead a team of Delivery Solution Architects. DSAs lead the post sales technical strategy for our largest customers, with a focus on ensuring use cases go into production as quickly and smoothly as possible. This requires orchestration skills and a solid understanding of Databricks technology and the Data+AI ecosystem. 

As a DSA Manager you will shape and monitor the post sales execution strategy for the customers in your region, in close collaboration with our sales, pre-sales and professional services teams as well as partners. You will be responsible for the DSA team in London and you will report to the DSA leader in NEMEA.

You will make investment decisions in collaboration with the sales and pre sales managers for your region. You will help shape and adjust the value proposition of the DSA role for your region and promote it in front of sales teams and customers. 

You will be technical sponsor and thought-leader to a select number of customers. You will hire and coach your team (of Delivery Solution Architects) to prioritize and work with different customer stakeholders up to C-level executives, with the goal of driving accelerated usage growth by getting use cases into production, faster. 

You and your team will contribute to the creation of assets to build the Delivery Solution Architect practice to and improve effectiveness and consistency in working with customers.

The impact you will have:

Manage a diverse team of Delivery Solution Architects to achieve customer, company, and team goals (usage growth, career growth and hiring) Assign accounts and distribute work across individuals for optimal customer coverage and team balance Inspire the team to be customer obsessed by understanding customer goals, their use cases, and Databricks technology Partner with Sales, pre Sales and professional services teams to accelerate growth of customers Work with teams to reduce customer risk and help your team with escalations. Lead team activities to monitor customer progress and forecast growth Provide input to grow and improve internal processes and customer success service offerings Promote cross functional programs, plans, documentation

What we look for:

Extensive experience in a customer facing role Experience leading a team of pre or post sale consultants/solution architects, technical account managers or customer success engineers. Experience in putting workloads or data products into production and running them, e.g. in a delivery architect, project manager, devops, or service/product owner role. Conversant with business issues our customers face today and likely big data use cases in different industries

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

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

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.