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

Apply Now

Lead Data Engineer

Davyhulme
3 days ago
Create job alert

About the RoleReporting to the Head of Data, Insights & Analytics you will lead a team of Data Engineers in the design, development and maintenance of Travel Counsellors’ data infrastructure. This role will be a high impact, multi-faceted working on data pipelines, our new strategic Data Platform and operationalising our analytical / data science solutions.

Principal Accountabilities

Support the design and implementation of data pipelines to ensure accurate, consistent and timely data across our analytical and reporting needs
Work closely with Data Scientists, Analysts and business SMEs to automate and scale our machine learning and AI capabilities
Support the development of our new cloud-based Data Platform, transforming systematic data into a business view for reporting and analytics
Take ownership of our existing Microsoft technology (SQL Server, SSIS, SSAS, SSRS) whilst delivering on our migration plans to cloud-based technology
Create and maintain comprehensive documentation for data processes and architectures. Provide training and support to team members and stakeholders.
Stay updated on industry trends and best practices in data engineering, advocating for continuous improvement within the team.
Lead data-related projects, ensuring timely delivery while balancing multiple priorities and stakeholder needs.

Benefits·       Competitive salary + annual bonus

·       Flexible hybrid working

·       Career development opportunities

·       25 days holiday (increasing to 28 after 5 years)

·       Enhanced Maternity/Paternity pay

·       1 day paid charity day

·       Company events and incentives

·       3x salary death in service benefit

·       Pension scheme

·       Private Medical Insurance or Healthcare Cash Plan

·       Free breakfast and beverages

Requirements

Highly proficient in SQL
Highly proficient in Python
Strong understanding of data modelling techniques, e.g. 3NF, Kimball
Experience using cloud-based data platforms and infrastructure, e.g. Snowflake, BigQuery etc
Experience building data integrations and understanding of best practices
Understanding of the development lifecycle and best practices
Desire to build relationships with an ability to deliver solutions to meet customers needs
Experience in deploying and maintaining machine learning models desirable
Experienced in the use of BI tools such as PowerBI / Tableau desirable
Understanding of the regulatory environment and the need for data to comply with GDPR

Related Jobs

View all jobs

Lead Data Engineer

Lead Data Engineer

Lead Data Engineer

Lead Data Engineer

Lead Data Engineer

Lead Data Engineer

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 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.

Why the UK Could Be the World’s Next Machine Learning Jobs Hub

Machine learning (ML) is becoming essential to industries across the globe—from finance and healthcare to retail, logistics, defence, and the public sector. Its ability to uncover patterns in data, make predictions, drive automation, and increase operational efficiency has made it one of the most in-demand skill sets in the technology world. In the UK, machine learning roles—from engineers to researchers, product managers to analysts—are increasingly central to innovation. Universities are expanding ML programmes, enterprises are scaling ML deployments, and startups are offering applied ML solutions. All signs point toward a surging need for professionals skilled in modelling, algorithms, data pipelines, and AI systems. This article explores why the United Kingdom is exceptionally well positioned to become a global machine learning jobs hub. It examines the current landscape, strengths, career paths, sector-specific demand, challenges, and what must happen for this vision to become reality.

The Best Free Tools & Platforms to Practise Machine Learning Skills in 2025/26

Machine learning (ML) has become one of the most in-demand career paths in technology. From predicting customer behaviour in retail to detecting fraud in banking and enabling medical breakthroughs in healthcare, ML is transforming industries across the UK and beyond. But here’s the truth: employers don’t just want candidates who have read about machine learning in textbooks. They want evidence that you can actually build, train, and deploy models. That means practising with real tools, working with real datasets, and solving real problems. The good news is that you don’t need to pay for expensive software or courses to get started. A wide range of free, open-source tools and platforms allow you to learn machine learning skills hands-on. Whether you’re a beginner or preparing for advanced roles, you can practise everything from simple linear regression to deploying deep learning models — at no cost. In this guide, we’ll explore the best free tools and platforms to practise machine learning skills in 2025, and how to use them effectively to build a portfolio that UK employers will notice.