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- Tasks: Lead and innovate data engineering teams while designing enterprise-scale data platforms.
- Company: Established UK tech firm focused on data-driven decision-making.
- Benefits: Competitive salary, remote-first work, and quarterly team meet-ups.
- Why this job: Take ownership of impactful data projects and shape the future of data engineering.
- Qualifications: Proven leadership in data engineering with strong technical skills in Azure, SQL, and Python.
- Other info: Join a dynamic team with opportunities for professional growth and collaboration.
The predicted salary is between 95000 - 130000 £ per year.
UK-based | Remote first (quarterly on-site in Reading)
£110,000 – £140,000 + benefits
We're working with a well-established UK technology business that sits at the intersection of data, property and decision-making. Data is core to how the organisation operates, and they're now looking for a Head of Data Engineering to take full ownership of their data platforms and engineering capability.
This role is about depth as much as leadership. You'll set the technical direction, stay close to the architecture, and build an environment where data engineers can do their best work, while ensuring platforms are reliable, scalable and commercially sound.
What you'll be responsible for:
- Owning the design and evolution of enterprise-scale data platforms and pipelines
- Setting engineering standards and acting as the senior technical authority for data engineering
- Leading and developing a team of experienced data engineers
- Ensuring operational excellence: availability, performance, cost control and incident management
- Partnering closely with product, software engineering, architecture, data science and security teams
- Making pragmatic architectural decisions that balance modern engineering practices with resilience and governance
What we're looking for:
- Proven experience leading data engineering teams while remaining technically hands-on
- Strong background designing and operating large-scale data platforms
- Deep experience within the Azure data ecosystem
- Excellent SQL and Python skills in production environments
- Experience with modern ETL/ELT patterns, CI/CD and infrastructure as code
- A pragmatic, commercially aware mindset. You understand why the platform exists, not just how
Working model:
This is a remote-first role within the UK, with an expectation to be on-site once per quarter for planning and collaboration.
Eligibility:
Applicants must already have the right to work in the UK, as sponsorship is not available for this position.
If you're a senior data engineering leader who still enjoys being close to the technology and wants real ownership rather than oversight, this is a role worth exploring.
Head of Data Engineering in Warrington employer: Develop
Contact Detail:
Develop Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Head of Data Engineering in Warrington
✨Tip Number 1
Network like a pro! Reach out to your connections in the data engineering field and let them know you're on the lookout for opportunities. You never know who might have a lead or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your past projects, especially those involving large-scale data platforms. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge. Be ready to discuss your experience with Azure, SQL, and Python, as well as your approach to leading data engineering teams. Confidence is key!
✨Tip Number 4
Don't forget to apply through our website! We make it easy for you to find roles that match your skills and aspirations. Plus, it shows you're serious about joining our team.
We think you need these skills to ace Head of Data Engineering in Warrington
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the job description. Highlight your experience in leading data engineering teams and your technical skills in SQL and Python. We want to see how you can bring value to our data platforms!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Share your passion for data engineering and how your background aligns with our needs. Don’t forget to mention your hands-on experience and leadership style – we love a good story!
Showcase Your Technical Skills: In your application, be sure to include specific examples of your work with large-scale data platforms and any modern ETL/ELT patterns you've implemented. We’re looking for someone who can set engineering standards and lead by example!
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you don’t miss out on any important updates. Plus, it’s super easy!
How to prepare for a job interview at Develop
✨Know Your Data Inside Out
Make sure you’re well-versed in the specifics of data platforms and engineering practices. Brush up on your knowledge of Azure, SQL, and Python, as these will likely come up during technical discussions. Being able to speak confidently about your past experiences with large-scale data platforms will set you apart.
✨Showcase Your Leadership Style
Prepare to discuss how you lead and develop teams. Think of examples where you've successfully guided data engineers and fostered a collaborative environment. Highlight your approach to setting engineering standards and how you ensure operational excellence within your team.
✨Be Pragmatic and Commercially Aware
Understand the business side of data engineering. Be ready to explain how your decisions have positively impacted the bottom line or improved efficiency. This role requires a balance between technical depth and commercial insight, so demonstrate that you grasp why the platform exists, not just how it works.
✨Prepare for Cross-Functional Collaboration
Since this role involves partnering with various teams, think about how you’ve successfully collaborated with product, software engineering, and data science teams in the past. Prepare examples that showcase your ability to make pragmatic architectural decisions while considering input from different stakeholders.
