Data Engineering Manager

Manchester
8 months ago
Applications closed

Related Jobs

View all jobs

Data Engineer

Data Scientist - London, UK (Fully REMOTE)

Python Data Engineer

Data Engineer

Data Engineer (Automation)

Mid Level Data Engineer

Role: Data Engineering Manager - Manchester, hybrid
The Team:
A highly passionate bunch, our data, analytics and AI team bring our unique software solutions to life. Our mission is to empower our customers and internal stakeholders to improve business performance and minimise risk by providing them with clean, reliable data and analytical models. We are with them to help protect their information, make informed decisions, deliver a personalised service and automate their workloads. Our engineers might be building data pipelines, modelling data, developing predictive models or automations for repeatable tasks or creation of data products.
The role:
Your role in the division is to lead the team developing our cloud data platform to further build-out our ‘single source of truth’ for company data. We have a recently implemented technology stack and clear direction of travel, so your initial objectives will be to understand our business data and team capabilities to then expand and improve our Kimball-model data warehouse in Azure, focusing on new datasets, pipeline resilience, performance and security. You will lead and coach the team in deploying tools and processes to ensure good practice is embedded, in line with our strategic themes of quality, efficiency, empowerment, transparency and governance. That means you will be conversant with data warehouse modelling, source control, CICD and Infrastructure as Code.
Our technology stack is based on Microsoft software: Azure, SQL Server and DevOps, using Terraform for infrastructure deployment. Our source data is also in Microsoft technology, currently on-premise in hosted data centres in the EU and US.
We currently manage our work in Kanban, with the support of a dedicated Delivery Lead, to respond to rapid growth in use-cases for our data.
Tasks & responsibilities include:

  • Deliver good software development lifecycle processes are used for all our software artifacts, including use of source control, unit testing, CICD, IaC
  • Deliver an enterprise data model considering all our current and likely future data sources
  • Manage the improvement of our Kimball-style data warehouse in Azure
  • Lead and coach a team of engineers to build and maintain the platform
  • Partner with our delivery lead to manage the strategic roadmap and tactical workflow, ensuring that work items are delivered on time and with high quality
  • Ability to communicate clearly with diverse teams, including across our geographic locations
  • Ability to identify when a business need is unclear or ambiguous and ask the right questions
  • Ability to translate a business need into a technical solution, considering scalability, security and resilience
  • Relentless approach to continuous improvement of both processes and individuals
    We think you’ll be a great fit if you have:
  • Experience of team leadership, especially of hybrid on- and off-shore teams
  • Experience of managing a team’s workload in collaboration with delivery, project or product professionals
  • Experience of modelling and building an enterprise data warehouse to support analytical workloads
  • Experience of using Azure services including Azure SQL Database, Data Factory, DevOps, Power BI
  • Experience of good SDLC practices: source control (git), CI/CD, test and release processes
  • Any experience using any of the following would also be a bonus in our environment: Dynamics CRM, Rabbit MQ, HubSpot, C# .NET development or legacy Microsoft data technologies (SSIS, SSRS)
    We are looking for the right person who is a team player who can communicate effectively and is comfortable working within a diversified, multi-cultural and multi-functional team, both locally and remote, understanding the perspectives of each partner. Above all, someone with the passion to drive and succeed in their own career.
    Experience in any of the above would help you to become productive in the job more quickly. We are genuinely committed to your success so, if you don’t quite meet all of our requirements yet, we encourage you to apply anyway and start a conversation

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.

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

Advertising machine learning jobs in the UK requires a different approach to most technical hiring. 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.

New Machine Learning Employers to Watch in 2026: UK and Global Companies Driving ML Innovation

Machine learning (ML) has transitioned from a specialised field into a core business capability. In 2026, organisations across healthcare, finance, robotics, autonomous systems, natural language processing, and analytics are expanding their machine learning teams to build scalable intelligent products and services. For professionals exploring opportunities on www.MachineLearningJobs.co.uk , understanding the companies that are scaling, winning investment, or securing high‑impact contracts is crucial. This article highlights the new and high‑growth machine learning employers to watch in 2026, focusing on UK innovators, international firms with significant UK presence, and global platforms investing in machine learning talent locally.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.