Data Engineering Manager

Leeds
1 week ago
Create job alert

Role: Data Engineering Manager

Salary: £65,000- £70,000 per annum

Location: Leeds (One day on site).

VIQU have partnered with a leading supply chain organisation who are looking to expand their data teams. The Data Engineering Manager will manage a team of eight to help with an on-going digital transformation. The ideal candidate will come from a technical background but has recently worked in a managerial role focused on mentoring, coaching, reviewing code, and standard setting. The role will focus on the development of the clients Databricks platform (AWS is preferred but open to Azure experience also), utilising Python and SQL, contribute to CI/CD pipelines, strategy development, cost optimisation and data governance frameworks. 

Job duties of the Data Engineering Manager: 

Manage a team of eight engineers, helping to mentor and coach the team.
Manage  the adoption of automated CI/CD pipelines.
Implement a new delivery roadmap.
Contribute to the development of a new Databricks system in AWS (AWS experience is preferred but they are open to managers with Azure experience).
Cost optimisation.
Establish data governance frameworks for secure handling of delivery information.
Requirements of the Data Engineering Manager:

6+ years experience in a hands on data engineer role, with over a years recent experience in a managerial role, coaching similar sized teams.
Deep knowledge of the Databricks platform.
Hands on Python development experience.
SQL optimisation.
Experience with large scale data pipeline optimisation.
Experience with Streaming and Batch Spark workloads.
Strong people management skills.
Role: Data Engineering Manager

Salary: £65,000- £70,000 per annum

Location: Leeds (One day on site).

To discuss this exciting opportunity in more detail, please APPLY NOW for a no obligation chat with your VIQU Consultant. Additionally, you can contact Jack McManus on (url removed).

If you know someone who would be ideal for this role, by way of showing our appreciation, VIQU is offering an introduction fee up to £1,000 once your referral has successfully started work with our client (terms apply).

To be the first to hear about other exciting opportunities, technology, and recruitment news, please also follow us at ‘VIQU IT Recruitment’ on LinkedIn, and Twitter: @VIQU_UK

Related Jobs

View all jobs

Data Engineering Manager

Data Engineering Manager

Data Engineering Manager

Senior SQL Data Engineer

Scrum Master

Engineering Manager

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.

Tips for Staying Inspired: How Machine Learning Pros Fuel Creativity and Innovation

Machine learning (ML) continues to reshape industries—from personalised e-commerce recommendations and autonomous vehicles to advanced healthcare diagnostics and predictive maintenance in manufacturing. Yet behind every revolutionary model lies a challenging and sometimes repetitive process: data cleaning, hyperparameter tuning, infrastructure management, stakeholder communications, and constant performance monitoring. It’s no wonder many ML professionals can experience creative fatigue or get stuck in the daily grind. So, how do machine learning experts keep their spark alive and continually generate fresh ideas? Below, you’ll find ten actionable strategies that successful ML engineers, data scientists, and research scientists use to stay innovative and push boundaries. Whether you’re an experienced practitioner or just breaking into the field, these tips can help you fuel creativity and discover new angles for solving complex problems.

Top 10 Machine Learning Career Myths Debunked: Key Facts for Aspiring Professionals

Machine learning (ML) has become one of the hottest fields in technology—touching everything from recommendation engines and self-driving cars to language translation and healthcare diagnostics. The immense potential of ML, combined with attractive compensation packages and high-profile success stories, has spurred countless professionals and students to explore this career path. Yet, despite the boom in demand and innovation, machine learning is not exempt from myths and misconceptions. At MachineLearningJobs.co.uk, we’ve had front-row seats to the real-life career journeys and hiring needs in this field. We see, time and again, that outdated assumptions—like needing a PhD from a top university or that ML is purely about deep neural networks—can mislead new entrants and even deter seasoned professionals from making a successful transition. If you’re curious about a career in machine learning or looking to take your existing ML expertise to the next level, this article is for you. Below, we debunk 10 of the most persistent myths about machine learning careers and offer a clear-eyed view of the essential skills, opportunities, and realistic paths forward. By the end, you’ll be better equipped to make informed decisions about your future in this dynamic and rewarding domain.

Global vs. Local: Comparing the UK Machine Learning Job Market to International Landscapes

How to evaluate opportunities, salaries, and work culture in machine learning across the UK, the US, Europe, and Asia Machine learning (ML) has rapidly transcended the research labs of academia to become a foundational pillar of modern technology. From recommendation engines and autonomous vehicles to fraud detection and personalised healthcare, machine learning techniques are increasingly ubiquitous, transforming how organisations operate. This surge in applications has fuelled an extraordinary global demand for ML professionals—data scientists, ML engineers, research scientists, and more. In this article, we’ll examine how the UK machine learning job market compares to prominent international hubs, including the United States, Europe, and Asia. We’ll explore hiring trends, salary ranges, workplace cultures, and the nuances of remote and overseas roles. Whether you’re a fresh graduate aiming to break into the field, a software engineer with an ML specialisation, or a seasoned professional seeking your next challenge, understanding the global ML landscape is essential for making an informed career move. By the end of this overview, you’ll be equipped with insights into which regions offer the best blend of salaries, work-life balance, and cutting-edge projects—plus practical tips on how to succeed in a domain that’s constantly evolving. Let’s dive in.