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- Tasks: Lead and innovate data engineering teams while designing enterprise-scale data platforms.
- Company: Established UK tech firm at the forefront of data and decision-making.
- Benefits: Competitive salary, remote-first work, and quarterly on-site collaboration.
- 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 innovation.
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 Hull employer: Develop
Contact Detail:
Develop Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Head of Data Engineering in Hull
✨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 or GitHub repository showcasing your projects, especially those involving Azure, SQL, and Python. This gives 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 and leadership experience. Be ready to discuss how you've set engineering standards and led teams in the past—this is your chance to shine!
✨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 Hull
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 your background aligns with what we're looking for!
Showcase Your Achievements: Don’t just list your responsibilities; show us what you’ve achieved! Use metrics and examples to demonstrate how you've improved data platforms or led successful projects. This helps us understand the impact you've made in previous roles.
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Explain why you're passionate about this role and how your experience makes you the perfect fit. We love seeing genuine enthusiasm and a clear understanding of our needs.
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 get all the updates. Plus, it shows you're keen on joining our team at StudySmarter!
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 impress the interviewers.
✨Showcase Your Leadership Style
Prepare to discuss your approach to leading data engineering teams. Think about examples where you've successfully developed talent or improved team performance. Highlight how you balance being hands-on with your leadership responsibilities, as this role requires both technical depth and strong leadership.
✨Understand the Business Impact
Demonstrate a clear understanding of how data engineering contributes to business goals. Be ready to discuss how you’ve made pragmatic architectural decisions that align with commercial objectives. This shows that you’re not just focused on the tech but also on how it drives value for the organisation.
✨Prepare for Collaborative Scenarios
Since this role involves partnering with various teams, think of examples where you’ve successfully collaborated with product, software engineering, or data science teams. Be prepared to discuss how you handle cross-functional challenges and ensure operational excellence across the board.
