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- Tasks: Lead the design and build of innovative data solutions for impactful projects.
- Company: Join a purpose-driven organisation reshaping data for environmental innovation.
- Benefits: Enjoy hybrid working, generous holidays, and a supportive culture with unique perks.
- Why this job: Be part of a tech-forward team making a real-world impact through data.
- Qualifications: 8 years in data engineering with expertise in SQL, Snowflake, Azure, and Python.
- Other info: Open to applicants who may not meet every requirement—apply anyway!
The predicted salary is between 55000 - 70000 £ per year.
Are you an experienced Data Engineer ready to step into a strategic, hands-on leadership role? We’re working with a purpose-driven organisation that’s reshaping how data supports environmental and regulatory innovation — and they need a Data Engineering Lead to help deliver their next-generation data platform. This is a chance to join a tech-forward, impact-led business based in the heart of Bristol. You’ll play a pivotal role in shaping and delivering a brand-new cloud-native data platform — the backbone of digital tools that serve major UK brands and internal teams alike.
What you’ll be doing:
- Lead the design and build of secure, scalable data pipelines using Azure Data Factory, Snowflake, and DBT
- Collaborate across Product, BI, Cloud, and IT to deliver data solutions that power real-world impact
- Optimise performance, enforce governance, and ensure seamless integration of APIs, external systems, and databases
- Own and evolve CI/CD pipelines using Azure DevOps, Git, and modern data practices
- Translate complex data into intuitive dashboards and tools with Power BI
- Be hands-on in everything from modelling and scripting to permissions and performance tuning
What we’re looking for:
- 8 years of experience in data engineering, with deep technical expertise across SQL, Snowflake, Azure, DBT, and Power BI
- Strong Python skills and experience integrating third-party systems via APIs
- A confident communicator who can bridge technical and non-technical teams
- Proven ability to deliver efficient, scalable solutions in fast-paced, regulated environments
- Someone who values diligence, accountability, and proactivity as much as technical excellence
Why join?
- A rare blend of purpose, scale, and flexibility
- £65,000 – £80,000 salary up to 10% bonus
- 28 days holiday bank holidays
- 7% employer pension, 5x salary life insurance, health cash plan, critical illness cover
- Flexible, hybrid working
- £250 home working setup
- Volunteer days, workcations, and a positive, impact-driven culture
This role offers a unique opportunity to shape both technology and purpose. If you’re excited by meaningful data work and want to be part of something bigger, we’d love to hear from you. If you are interested, but don’t think you tick all the boxes, we are still keen to hear from you.
Lead Data Engineer employer: SR2 REC LTD
Contact Detail:
SR2 REC LTD Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Data Engineer
✨Tip Number 1
Familiarise yourself with the specific technologies mentioned in the job description, such as Azure Data Factory, Snowflake, and DBT. Having hands-on experience or relevant projects to discuss can really set you apart during conversations.
✨Tip Number 2
Showcase your leadership skills by preparing examples of how you've successfully led data engineering projects in the past. Be ready to discuss how you collaborated with cross-functional teams to deliver impactful solutions.
✨Tip Number 3
Brush up on your communication skills, especially in translating complex technical concepts into layman's terms. This will be crucial when discussing your experience with both technical and non-technical stakeholders.
✨Tip Number 4
Research the company’s mission and values, particularly their focus on environmental and regulatory innovation. Being able to articulate how your personal values align with theirs can make a strong impression during interviews.
We think you need these skills to ace Lead Data Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data engineering, particularly with SQL, Snowflake, Azure, and DBT. Use specific examples to demonstrate your technical expertise and leadership skills.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for data and its impact on environmental and regulatory innovation. Mention how your experience aligns with the company's mission and the specific role of Lead Data Engineer.
Highlight Key Projects: In your application, include details about key projects where you've designed and built data pipelines or worked with cloud-native platforms. Emphasise your hands-on experience with tools like Azure Data Factory and Power BI.
Showcase Soft Skills: Don't forget to mention your communication skills and ability to collaborate across teams. Provide examples of how you've bridged the gap between technical and non-technical stakeholders in previous roles.
How to prepare for a job interview at SR2 REC LTD
✨Showcase Your Technical Expertise
Be prepared to discuss your experience with SQL, Snowflake, Azure, DBT, and Power BI in detail. Highlight specific projects where you've successfully implemented these technologies, as this will demonstrate your hands-on skills and technical depth.
✨Communicate Effectively
As a Lead Data Engineer, you'll need to bridge the gap between technical and non-technical teams. Practice explaining complex data concepts in simple terms, and be ready to share examples of how you've facilitated collaboration across different departments.
✨Demonstrate Leadership Qualities
Prepare to discuss your leadership style and experiences. Think of instances where you've led a team or project, focusing on how you motivated others, resolved conflicts, and ensured successful outcomes in fast-paced environments.
✨Emphasise Your Problem-Solving Skills
Be ready to tackle hypothetical scenarios or case studies during the interview. Show how you approach problem-solving, particularly in optimising data pipelines and ensuring seamless integration of systems, as this is crucial for the role.
