Lead Data Engineer

Frasers Group
Clayton-le-Moors
6 months ago
Applications closed

Related Jobs

View all jobs

Lead Data Engineer

Lead Data Engineer - Snowflake, DBT, Airflow - London - £100k

Lead Data Engineer - Databricks

Lead/Senior Data Engineer

Lead Data Engineer

Lead Data Engineer (AD -Consulting) - Exclusive

Company Description

At Frasers Group we’re rethinking retail. Through digital innovation and unique customer experiences, we’re serving our consumers with the world’s best sports, premium and luxury brands globally. As a leader in the industry, we’re elevating the retail experience for our consumers providing flexible and convenient ways to pay across our collection of established brands, including Studio, Sports Direct, FLANNELS, USC, Frasers, and GAME

Frasers Group Financial Services is the next chapter of elevation for the Frasers Group.
We fear less and do more. Our people are forward thinkers who are driven to operate outside of their comfort zone to change the future of retail, embracing challenges along the way. The potential to elevate your career is massive, the experience unrivalled.

Why join us?

Our purpose – we are elevating the lives of the many with access to the world’s best brands and experiences

Frasers Group Financial Services is committed to delivering a positive colleague experience and to be able to make the most of it you need to immerse yourself into delivering on our principles:

Think without limits - Think fast, think fearlessly, and take the team with youOwn it and back yourself - Own the basics, own your role and own the resultsBe relevant - Relevant to our people, our partners and the planet

Are you ready to join the Fearless?

Job Description

The role of the Lead Data Engineer is to lead the design, development, and maintenance of the organisation's data infrastructure. The role involves overseeing the efficient, reliable, and secure collection, storage, and processing of data, which is critical for enabling data-driven decision-making across FGFS.

The Team Lead will help manage and mentor a team of data engineers, working collaboratively with cross-functional teams to implement data solutions, optimise data pipelines, and drive the overall data strategy, ensuring data integrity, security, and accessibility across FGFS. The Team Lead will also play a key role in strategic planning, process improvement, and aligning data initiatives with business goals.

Lead the design, development, and maintenance of scalable and efficient data pipelines for extracting, transforming, and loading data from multiple sources. Oversee the team's efforts in building and optimising data pipelines, ensuring alignment with organisational goals and performance standards. Manage and mentor a team of data engineers, providing guidance, support, and professional development opportunities. Oversee the diagnosis and resolution of complex data-related issues within the platform, ensuring prompt and effective support and maintenance of data systems. Implement best practices for monitoring and alerting to proactively address potential issues. Act as a primary liaison between the data engineering team, spoke analysts, and other key stakeholders to align data solutions with business needs. Ensure the team adheres to data governance policies, regulatory requirements, and data security best practices. Oversee the creation and maintenance of comprehensive documentation of data engineering processes. Regularly report on system performance, data quality, and pipeline health to senior management and other stakeholders. Drive the continuous improvement of data engineering practices by staying current with industry trends, emerging technologies, and best practices. Lead initiatives to implement innovative solutions and improvements, ensuring the data engineering team's approach remains efficient, scalable, and effective.

Qualifications

Required

Good knowledge of enterprise data warehousing, data integration and Business Intelligence (BI) reporting. Well versed with cloud-based data warehouse solutions including Snowflake. Knowledge of DBT and different ingest tools such as Stitch, Fivetran and Snowpipe. Significant SQL experience. Experience with leading and mentoring junior members of a team. Comfortable with working in a high pressure environment and working to tight deadlines Strong understanding of Data Governance best practice

Desirable

Working knowledge of Python. Experience with modelling data for Microsoft PowerBI. Knowledge of best practice for data modelling and architecture. Prior Financial Services experience

Non-technical required:

Excellent critical thinking and solution creation skills Ability to deliver in a fast-paced and dynamic environment.

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Jobs

Rural-Remote Machine Learning Jobs: Finding Balance Beyond the Big Cities

Over the past decade, machine learning (ML) has transformed from a niche research domain into a pervasive technology underpinning everything from recommendation systems and voice assistants to financial forecasting and autonomous vehicles. Historically, the UK’s major tech hubs—particularly London—have been magnets for top ML talent and corporate headquarters. However, remote work has become mainstream, and many ML professionals are realising they can excel in their field while living far beyond the city limits. At MachineLearningJobs.co.uk, we’ve observed a growing interest in positions that allow for a rural lifestyle or a coastal environment, often reflected in search terms like “ML remote countryside” or “tech jobs by the sea.” This surge is no coincidence. Flexible work policies, better rural broadband, and the nature of machine learning tasks—much of which can be done through cloud platforms—are bringing new opportunities to those who wish to swap urban hustle for fresh air and scenic views. Whether you’re a data scientist, ML engineer, researcher, or product manager, a rural or seaside move could reinvigorate your work-life balance. In this article, we’ll unpack why rural-remote ML jobs are on the rise, how you can navigate the challenges of leaving the city, and what you need to do to thrive in a machine learning career beyond the M25. If you’ve dreamt of looking up from your laptop to rolling fields or ocean waves, keep reading—your rural ML role might be closer than you think.

Jobs

Quantum-Enhanced Machine Learning—Propelling AI into the Next Frontier

Machine learning (ML) has revolutionised how we interpret data, build predictive models, and create intelligent applications. From recommendation engines and self-driving cars to advanced genomics and natural language processing, ML solutions are integral to nearly every corner of modern life. However, as data complexity and model size continue to skyrocket, the computational demands placed on ML systems grow in tandem—often pushing even high-performance classical computers to their limits. In recent years, quantum computing has emerged as a tantalising solution to these challenges. Unlike traditional digital systems, quantum computers exploit quantum mechanics—superposition and entanglement—to process information in ways that defy conventional logic. As these machines mature, they promise exponential speed-ups for certain tasks, potentially reshaping how we approach AI and data-intensive challenges. What does this mean for machine learning? Enter quantum-enhanced ML, a new frontier where quantum processors and classical ML frameworks unite to accelerate model training, tackle high-dimensional data, and solve complex optimisation tasks more efficiently. In this article, we will: Unpack the current state of machine learning, highlighting key bottlenecks. Provide a concise overview of quantum computing—why it’s radical and how it differs from classical technology. Examine potential breakthroughs in quantum-enhanced ML, including real-world use cases and technical approaches. Explore the roles and skill sets that will define this quantum-AI era, with guidance on how to prepare. Discuss the roadblocks (like hardware maturity and ethical concerns) and how they might be addressed in the years to come. If you’re a machine learning engineer, data scientist, or simply an AI enthusiast fascinated by the next wave of computational innovation, read on—quantum computing could become an integral part of your future toolkit, opening up job opportunities and reimagining what ML can achieve.

Jobs

Machine Learning Jobs at Newly Funded UK Start-ups: Q3 2025 Investment Tracker

Machine learning (ML) has become the beating heart of modern tech innovation, powering breakthroughs in healthcare, finance, cybersecurity, robotics, and more. Across the United Kingdom, this surge in ML-driven solutions is fueling the success of countless start-ups—and spurring demand for talented machine learning engineers, data scientists, and related professionals. If you’re eager to join a high-growth ML company or simply want to keep tabs on the latest trends, this Q3 2025 Investment Tracker will guide you through the newly funded UK start-ups pushing the boundaries of ML. In this article, we’ll highlight key developments from Q3 2025, delve into the most promising newly funded ventures, and shed light on the machine learning roles they’re urgently seeking to fill. Plus, we’ll show you how to connect with these employers via MachineLearningJobs.co.uk, a dedicated platform for ML job seekers. Let’s dive in!

🍪 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.