At a Glance
- Tasks: Lead a dynamic data engineering team and drive a major platform transformation.
- Company: Major UK retailer revolutionising its data usage with a cloud-native approach.
- Benefits: Competitive salary, hybrid working, and opportunities for professional growth.
- Other info: Fast-paced, agile environment with a focus on modern engineering practices.
- Why this job: Be at the forefront of data innovation and make a significant impact.
- Qualifications: Proven leadership in data engineering with hands-on experience in Snowflake and dbt.
The predicted salary is between 100000 - 125000 € per year.
A major UK retailer is transforming how it uses data and they need an experienced Head of Data Engineering to lead the charge. This is a senior, hands-on leadership role at the heart of a cloud-native data platform build. You'll be setting the technical direction for data engineering, leading a growing team, and owning the modernised platform long after the initial build is complete.
What you'll be doing:
- Leading and growing a data engineering team through a major platform transformation
- Setting the technical direction for data pipelines, architecture, and tooling across a Snowflake Medallion environment
- Overseeing the migration of legacy SQL Server, SSRS, and Business Objects onto the modern platform
- Owning the data engineering function through delivery and into the steady-state — you build it, you run it
- Working closely with integrations, reporting, and BA teams to ensure end-to-end delivery
- Acting as the senior escalation point for data engineering decisions across a fast-paced, agile programme
- Driving adoption of dbt and modern engineering best practices across the team
What we're looking for:
- Proven leadership experience — real people management, not just a senior engineer with a title
- Deep hands-on experience with Snowflake, ideally including Medallion architecture
- Strong dbt and SQL/Python skills — this role requires someone who can still get into the detail
- Azure data infrastructure experience
- A track record of delivering at pace in agile, high-velocity environments
- Experience migrating off legacy data estates
- UK right to work — no sponsorship available
The stack: Snowflake · dbt · Azure One Lake · Power BI · Datadog · Python · SQL
Head of Data Enigneering in Warrington employer: Morgan McKinley
As a major UK retailer, we pride ourselves on fostering a dynamic and inclusive work culture that champions innovation and collaboration. Our Manchester-based team enjoys a hybrid working model, competitive salary, and ample opportunities for professional growth, making it an ideal environment for those looking to make a significant impact in the data engineering field. Join us to lead transformative projects while benefiting from our commitment to employee development and a supportive workplace atmosphere.
StudySmarter Expert Advice🤫
We think this is how you could land Head of Data Enigneering in Warrington
✨Tip Number 1
Network like a pro! Reach out to your connections in the data engineering field, especially those who might know about opportunities at major retailers. A personal recommendation can make all the difference in landing that interview.
✨Tip Number 2
Show off your skills! Prepare a portfolio or case studies showcasing your experience with Snowflake and dbt. When you get the chance to chat with potential employers, having tangible examples of your work will set you apart from the crowd.
✨Tip Number 3
Stay updated on industry trends! Follow relevant blogs, podcasts, and forums to keep your knowledge fresh. This will not only help you in interviews but also show that you're genuinely passionate about data engineering.
✨Tip Number 4
Apply through our website! We’ve got a streamlined application process that makes it easy for you to showcase your skills. Plus, it gives us a better chance to see your application in the right light!
We think you need these skills to ace Head of Data Enigneering in Warrington
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the Head of Data Engineering role. Highlight your leadership experience and hands-on expertise with Snowflake, dbt, and Azure to catch our eye!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Share your passion for data engineering and how you’ve led teams through transformations. We want to see your personality and what makes you the perfect fit for our team.
Showcase Your Technical Skills:Don’t shy away from getting into the nitty-gritty! Detail your experience with data pipelines, architecture, and any relevant projects you've worked on. We love seeing candidates who can dive deep into technical discussions.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity. Let’s get started on this journey together!
How to prepare for a job interview at Morgan McKinley
✨Know Your Tech Stack Inside Out
Make sure you’re well-versed in Snowflake, dbt, and Azure. Brush up on your SQL and Python skills too! Be ready to discuss how you've used these technologies in past projects, especially in a hands-on capacity.
✨Showcase Your Leadership Skills
This role is all about leading a team, so be prepared to share specific examples of how you've managed people and driven a team towards success. Highlight your experience in transforming data engineering functions and how you’ve fostered a collaborative environment.
✨Prepare for Technical Challenges
Expect some technical questions or case studies during the interview. Think about how you would approach migrating legacy systems to a modern platform. Practise explaining your thought process clearly and concisely.
✨Understand the Business Context
Research the company and its data transformation goals. Be ready to discuss how your vision aligns with their objectives and how you can contribute to their success. Showing that you understand their business will set you apart from other candidates.
