National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Head of Data Engineering

The Progeny Group
united kingdom
1 month ago
Applications closed

Related Jobs

View all jobs

Head of Data Engineering

Head of Data Engineering

Head of Data Engineering & Governance

Head of Data Engineering & AI

Head of Data Engineering & Governance

Head of Data Engineering & AI

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

National AI Awards 2025

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.

How to Present Machine Learning Solutions to Non-Technical Audiences: A Public Speaking Guide for Job Seekers

Machine learning is driving change across nearly every industry—from retail and finance to health and logistics. But while the technology continues to evolve rapidly, the ability to communicate it clearly has become just as important as building the models themselves. Whether you're applying for a junior ML engineer role, a research position, or a client-facing AI consultant job, UK employers increasingly expect candidates to explain complex machine learning solutions to non-technical audiences. In this guide, you’ll learn how to confidently present your work, structure your message, use simple visuals, and explain the real-world value of machine learning in a way that makes sense to people without a background in data science.

Machine Learning Jobs UK 2025: 50 Companies Hiring Now

Bookmark this page—we refresh the Hotlist every quarter so you always know who’s really scaling their ML teams. The UK’s National AI Strategy, a £2 billion GenAI accelerator fund and a record flow of private capital have kicked ML hiring into overdrive for 2025. Whether you build production‑grade LLM services or optimise on‑device models for edge hardware, employers need your skills now. Below you’ll find 50 organisations that advertised UK‑based machine‑learning vacancies or announced head‑count growth during the past eight weeks. They’re grouped into five quick‑scan categories so you can jump straight to the type of employer—and mission—that excites you. For each company we list: Main UK hub Example live or recent vacancy Why it’s worth a look (stack, impact, culture) Search any employer on MachineLearningJobs.co.uk to see real‑time adverts, or set a free alert so fresh openings drop straight in your inbox.

Return-to-Work Pathways: Relaunch Your Machine Learning Career with Returnships, Flexible & Hybrid Roles

Returning to work after an extended break can feel like starting from scratch—especially in a specialist field like machine learning. Whether you paused your career for parenting, caring responsibilities or another life chapter, the UK’s machine learning sector now offers a variety of return-to-work pathways. From structured returnships to flexible and hybrid roles, these programmes recognise the transferable skills and resilience you’ve developed, pairing you with mentorship, upskilling and supportive networks to ease your transition back. In this guide, you’ll discover how to: Understand the current demand for machine learning talent in the UK Leverage your organisational, communication and analytical skills in ML contexts Overcome common re-entry challenges with practical solutions Refresh your technical knowledge through targeted learning Access returnship and re-entry programmes tailored to machine learning Find roles that fit around family commitments—whether flexible, hybrid or full-time Balance your career relaunch with caring responsibilities Master applications, interviews and networking specific to ML Learn from inspiring returner success stories Get answers to common questions in our FAQ section Whether you aim to return as an ML engineer, research scientist, MLOps specialist or data scientist with an ML focus, this article will map out the steps and resources you need to reignite your machine learning career.