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

Nominate & Attend

Data Engineering Manager

Michael Page
6 months ago
Applications closed

Related Jobs

View all jobs

Data Engineering Manager

Data Engineering Manager

Data Engineering Manager

Data Engineering Manager

Data Engineering Manager

Data Engineering Manager

Leading Transportation organisation are seeking to hire a Head of Data & Engineering in this newly created role. You will lead a team of developers and analysts to provide a robust data platform on their journey to self-serve information, providing insight and analysis with the sole purpose of providing excellent service to customers. Outside of Data Engineering you will fulfil a broad remit across, Data Architecture, Security and Data Quality ManagementClient DetailsLeading Transportation organisationDescriptionLeading Transportation organisation are seeking to hire a Head of Data & Data Engineering in this newly created role. You will lead a team of developers and analysts to provide a robust data platform on their journey to self-serve information, providing insight and analysis with the sole purpose of providing excellent service to customers. Outside of Data Engineering you will fulfil a broad remit across, Data Architecture, Data Security and Data Quality Management.Dimensions of the role:Deliver a wide range of projects with internal and external suppliers and have autonomy over an annual budget of £1M - £2M.Projects will typically consist of contributing to 3-7 smaller projects and 1 - 2 larger projects.Manage a team of 3 staff with the scope to hire additional headcount in 2025Strategy & Planning, typically annually and up to 3 years in advance. Key Responsibilities:Lead and manage the Data Engineering team, by providing strategic direction, and fostering a high-performing and collaborative working environment to ensure alignment with business goals, foster innovation and enhance productivity.Develop and implement a robust data engineering strategy that aligns with the IT and Digital Services Strategy and Data Strategy by providing alignment with business objectives, engagement with key stakeholders, assessment of the current data landscape, defining clear objectives, and developing a data governance framework, to ensure a robust data engineering strategy that aligns with business goalsOverseeing the development, implementation and management of a robust data platform ecosystem to leverage the power of data and AI initiatives by setting measurable goals such as; reducing operational costs, increasing data accessibility and by designing and building a scalable and flexible Azure Cloud environmentSupport ETL common data structure and business intelligence architectures by designing and implementing ETL processes, establishing common data structures, and developing business intelligence architectures to provide improved data quality and consistency and operational efficiencyChampion the adoption of data-driven decision-making across the organisation by securing leadership buy-in, articulating a clear vision and setoff measurable goals for the adoption of data driven practices, and through training and education, to ensure significant improvements in efficiency, customer satisfaction, and overall organisational performance.Lead on the build of a data community through the creation of cross functional working, shared platforms and data stewardship where communities of data engineers and analysts work together on stable, accurate and assured data sets to improve decisions and performance.Foster a culture of service excellence and continuous improvement within the team by developing and implementing training programs to ensure the team has the skills and knowledge to deliver high-quality services.Lead the development and execution of a data governance framework by defining its objectives and scope, establishing a governance structure, developing policies and standards, and implementing data management processes to ensure data quality, regulatory compliance, data security, operational efficiency and strategic decision making.Oversee the implementation and integration of big data technologies and tools, including a focus on optimising performance and efficiency for AI workloads by selecting relevant technologies and tools, designing and implementing data pipelines, and ensuring data quality and governance, to enhance the quality and usability of data to also foster a culture of innovationLead on performance improvements by collaborating with IT and Digital Services Team senior team to identify data-driven solutions to business challenges ProfileKey Skills and Experience:Degree in Data Science, Computer Science, Information Technology, or a related field.Significant experience of developing and delivering data strategies.Demonstrable experience in leading and managing data platform development and operations within a large organisation.In-depth knowledge of data platform technologies, including Azure data warehouses, data lakes, and data governance tools.Knowledge of optimising data pipelines, pipeline architectures and integrated datasets.Demonstrable knowledge of working with and understanding data architecture principles and best practice.Experience of procuring and implementing cloud-based data management solutions.Experience of implementing data security and compliance frameworks.Excellent communication and interpersonal skills, with the ability to collaborate effectively with technical and non-technical stakeholders.Experience of leading a team and providing solutions to data challenges.Experience with scripting languages (e.g., Python, SQL)Job OfferOpportunity to work on a major Data Transformation ProgrammeOpportunity to drive Data Strategy, Platforms and Growth

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.

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.

LinkedIn Profile Checklist for Machine Learning Jobs: 10 Tweaks to Drive Recruiter Interest

The machine learning landscape is rapidly evolving, with demand soaring for experts in modelling, algorithm tuning and data-driven insights. Recruiters hunt for candidates proficient in Python, TensorFlow, PyTorch and MLOps processes. A generic profile simply won’t cut it. Our step-by-step LinkedIn for machine learning jobs checklist covers 10 targeted tweaks to ensure your profile ranks in searches and communicates your technical impact. Whether launching your ML career or seeking leadership roles, these optimisations will sharpen your professional narrative and boost recruiter engagement.