Head of Data Engineering

The Progeny Group
united kingdom
11 months ago
Applications closed

Related Jobs

View all jobs

Data Engineer

Lead Data Scientist / Deep Learning Practitioner

Lead Data Scientist / Deep Learning Practitioner

Lead Data Scientist - Deep Learning Practitioner

Lead Data Scientist / Deep Learning Practitioner

Data Scientist / Statistician (Model Developer)

Head of Data Engineering

Department:Technology

Employment Type:Full Time

Location:Nationwide, UK (with occasional travel)


Description

As Head of Data Engineering, you will join our growing Data team to build and shape our Data Engineering function. Taking a hands-on approach, you will lead the design and management of our data infrastructure, architecture, pipelines, and solutions. With excellent leadership skills and interpersonal skills, you will be a natural communicator with the ability to scale and lead a high-performing team.

Please note this opportunity offers home based working but will require occasional travel to our offices.


Key Responsibilities

  • Shaping and developing data engineering capabilities and influencing the direction of the team.
  • Being the SME on design, development, and deployment of data ETL pipelines using Azure Data Factory, Azure Synapse, and other technologies to transform and access data from on-prem and cloud structures.
  • Developing high quality data pipelines and adopting engineering principles including domain driven design, test driven development, and clear separation of concerns.
  • Shaping the overall strategic data and analytical capabilities and influencing adoption of best practises to continuously improve standards across the team.
  • Building and leading the Data Engineering team to support development, continuous improvement, and identify skills and educational requirements.
  • Developing complex data products and solutions whilst managing projects and balancing the need for delivery.
  • Building relationships with internal and external stakeholders and influencing a data-driven culture.


Skills, Knowledge and Expertise

  • Demonstrable experience of building Data Engineering capabilities and frameworks from start to finish.
  • Experience working in a regulated environment, ideally in the provision of financial or legal services.
  • Previous experience in designing enterprise Data Models for Business Intelligence and key systems such as CRM’s.
  • Strong knowledge of database architecture and data warehousing.
  • Experience using Azure Data Factory, Azure Synapse, and similar technologies.
  • A natural leader with the ability to guide cultural change and foster collaboration.
We may close this vacancy early if we receive sufficient applications. Therefore, if you are interested, please submit your application as early as possible.


Benefits

  • 30 days holiday plus public holidays
  • 3 days of celebratory leave (to be used for your birthday, wellbeing, volunteering, or other celebratory events important to you.
  • Private medical insurance, 24/7 digital GP and health advice
  • Employee assistance programme providing support for your mental and physical health
  • Group pension scheme
  • Life assurance scheme
  • Eyecare vouchers
  • Enhanced family leave
  • Referral scheme

#J-18808-Ljbffr

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.

Products

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.

Jobs

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.

Careers

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.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.