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- Tasks: Lead data engineering strategy and build scalable data pipelines for analytics.
- Company: Global Food & Beverage organisation investing in data and analytics.
- Benefits: Competitive salary, 30% bonus, hybrid work model, and leadership opportunities.
- Why this job: Shape the future of data engineering and make a real impact on business growth.
- Qualifications: Proven experience in data engineering, strong technical skills, and team leadership.
- Other info: Join a dynamic team with high autonomy and career development potential.
The predicted salary is between 79200 - 110000 £ per year.
We’re delighted to be partnering exclusively with a global Food & Beverage organisation on their search for a Head of Data & Analytics Engineering. This is a pivotal leadership hire for an award-winning group that’s investing heavily in its data platform and analytics foundations, and is looking for someone to shape the data engineering strategy as the business continues to scale.
You’ll lead the data engineering function end-to-end, defining how data is ingested, modelled, and made available across the organisation, while building and leading a high-performing engineering team in a modern, cloud-based environment.
What you can expect:
- A senior, high-autonomy role with ownership of the Data & Analytics Engineering vision and roadmap, underpinning BI, analytics, and AI across the business.
- Responsibility for shaping and delivering the data hydration strategy, building scalable data pipelines and platforms that support self-service analytics and advanced use cases.
- A highly visible role partnering closely with senior stakeholders across technology and the wider business to prioritise initiatives and ensure data products deliver real business value.
- The opportunity to build and lead a growing Data Engineering team, setting technical standards, embedding best practice, and developing engineering capability across the organisation.
- Exposure to vendor and partner management, with accountability for delivery quality, timelines, and budget.
Desired background / skillset:
- Proven experience leading Data Engineering or Analytics Engineering functions within a multichannel business.
- Strong hands-on technical background across modern data platforms (cloud data lakes/warehouses, ETL/ELT, SQL, Python), with the ability to operate strategically at leadership level.
- Experience designing and delivering scalable, production-grade data pipelines that support BI, analytics, and AI use cases.
- Tech wise, experience with Azure & Databricks is highly desirable.
- A confident communicator and stakeholder partner, able to translate technical concepts into clear business outcomes.
- Experience building, mentoring, and developing high-performing engineering teams.
This is a rare opportunity to step into a genuinely influential Head-of role, with the support, backing, and autonomy to build the data engineering foundations that enable analytics and AI at scale.
Sound like a bit of you? Great! Please apply with an up-to-date CV and we can take it from there.
Data Engineering Manager in London employer: TRIA
Contact Detail:
TRIA Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineering Manager in London
✨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 the inside scoop on a role that’s perfect for you.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your projects, especially those involving cloud data platforms and scalable data pipelines. 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 and leadership experience. Be ready to discuss how you've shaped data strategies in the past and how you can do it again in this new role.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we’re here to support you every step of the way!
We think you need these skills to ace Data Engineering Manager in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Engineering Manager role. Highlight your experience in leading data engineering functions and any relevant technical skills, like Azure and Databricks, that match what we're looking for.
Showcase Your Leadership Skills: Since this is a senior role, don’t forget to showcase your leadership experience. Talk about how you've built and mentored high-performing teams, and how you’ve shaped data strategies in previous roles.
Be Clear and Concise: When writing your application, keep it clear and concise. Use straightforward language to explain your achievements and how they relate to the responsibilities of the role. We want to see your impact!
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’re considered for this exciting opportunity with us!
How to prepare for a job interview at TRIA
✨Know Your Data Engineering Fundamentals
Brush up on your knowledge of data platforms, ETL/ELT processes, and cloud technologies like Azure and Databricks. Be ready to discuss how you've applied these in previous roles, as this will show your hands-on experience and strategic thinking.
✨Showcase Leadership Skills
Prepare examples that highlight your experience in leading teams and shaping data strategies. Think about specific challenges you've faced and how you motivated your team to overcome them. This will demonstrate your capability to build and mentor high-performing engineering teams.
✨Communicate Clearly with Stakeholders
Practice translating complex technical concepts into business outcomes. You might be asked how you would communicate data strategies to non-technical stakeholders, so having clear, concise examples ready will help you shine in this area.
✨Demonstrate Your Vision for Data Engineering
Be prepared to discuss your vision for the data engineering function within the organisation. Think about how you would approach building scalable data pipelines and supporting self-service analytics, as this shows your forward-thinking mindset and alignment with the company's goals.
