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- Tasks: Lead the creation of a centralised enterprise data warehouse and develop scalable data pipelines.
- Company: Join a forward-thinking tech company focused on innovation and data-driven solutions.
- Benefits: Enjoy flexible working options and opportunities for professional growth.
- Why this job: Shape impactful projects from scratch in an agile, collaborative environment.
- Qualifications: Strong SQL and Python skills, experience with cloud platforms and data modelling required.
- Other info: Mentorship opportunities available to help you grow in the data space.
The predicted salary is between 48000 - 84000 £ per year.
We’re supporting a forward-thinking tech company on the lookout for a Senior Data Engineer to lead the build of a brand-new, centralised enterprise data warehouse — the company’s single source of truth.
This is a high-impact, greenfield role where you’ll own everything from architecture to deployment. If you\’re passionate about data, thrive in agile teams, and want to shape something from the ground up — this is for you.
What you’ll do:
- Design and build a cloud-native data warehouse
- Develop scalable ETL/ELT pipelines and dimensional models (Kimball, Data Vault, etc.)
- Integrate multiple data sources (cloud & on-prem)
- Ensure high data quality, performance and reliability
- Collaborate with engineers, analysts and product teams
- Lead best practices and mentor others in the data space
What They’re looking for:
- Strong SQL and Python skills
- Experience with dbt, Snowflake (or similar), and cloud platforms
- Solid data modelling background
- Familiar with APIs (REST/SOAP), Git, CI/CD, and test automation
- Strong communicator with a proactive, problem-solving mindset
Find out more
If you would like to have a confidential conversation and find out more about this opportunity, then get in touch with at Johnathan Potts Search 5.0 on 07880850450 or click apply
Contact Detail:
Search 5.0 Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Engineer
✨Tip Number 1
Familiarise yourself with the latest trends in data engineering, especially around cloud-native solutions and data warehousing. This will not only help you in interviews but also show your genuine interest in the role.
✨Tip Number 2
Network with current data engineers or professionals in similar roles on platforms like LinkedIn. Engaging in discussions about best practices and challenges can provide insights that may be beneficial during your interview.
✨Tip Number 3
Prepare to discuss specific projects where you've implemented ETL/ELT pipelines or worked with data modelling techniques like Kimball or Data Vault. Real-world examples will demonstrate your expertise and problem-solving skills.
✨Tip Number 4
Brush up on your SQL and Python skills, as these are crucial for the role. Consider working on small projects or challenges that allow you to showcase your technical abilities and understanding of data integration.
We think you need these skills to ace Senior Data Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with SQL, Python, and any relevant cloud platforms like Snowflake. Emphasise your data modelling skills and any previous work with ETL/ELT pipelines.
Craft a Compelling Cover Letter: In your cover letter, express your passion for data and your desire to lead projects from the ground up. Mention specific examples of how you've successfully integrated multiple data sources or improved data quality in past roles.
Showcase Your Technical Skills: If you have experience with dbt, Git, or CI/CD, make sure to include this in your application. Consider providing links to any relevant projects or repositories that demonstrate your technical expertise.
Highlight Collaboration Experience: Since the role involves working with engineers, analysts, and product teams, include examples of how you've successfully collaborated in agile environments. This will show your strong communication skills and proactive mindset.
How to prepare for a job interview at Search 5.0
✨Showcase Your Technical Skills
Be prepared to discuss your experience with SQL, Python, and any relevant tools like dbt or Snowflake. Bring examples of past projects where you designed data warehouses or built ETL pipelines to demonstrate your expertise.
✨Understand the Company’s Data Needs
Research the company’s current data architecture and challenges they might face. This will help you tailor your answers to show how you can contribute to their specific goals and needs in building a centralised data warehouse.
✨Emphasise Collaboration
Since the role involves working with engineers, analysts, and product teams, highlight your teamwork skills. Share examples of how you've successfully collaborated in agile environments and led best practices in previous roles.
✨Prepare for Problem-Solving Questions
Expect questions that assess your problem-solving abilities, especially related to data quality and performance issues. Think of scenarios where you identified and resolved data-related problems, and be ready to discuss your thought process.
