Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Own and optimise an Azure-based data warehouse for a fast-growing organisation.
- Company: Join a collaborative team that values innovation and curiosity in London.
- Benefits: Enjoy a competitive salary of £80,000 - £90,000 plus flexible benefits.
- Why this job: Make a real impact on data strategy using cutting-edge cloud technologies.
- Qualifications: 5+ years in data engineering with strong skills in Python and Azure services.
- Other info: Ideal for those passionate about data and eager to tackle new challenges.
The predicted salary is between 64000 - 96000 £ per year.
Job Description
💼 Data Warehouse Solution Engineer
📍 London | 💰 £80,000 – £90,000 (flexible for exceptional experience) + benefits
We’re searching for a skilled data engineering professional who enjoys solving complex problems and turning data into actionable insights. This role sits at the heart of a collaborative, forward-thinking team that values innovation, curiosity, and a willingness to take on new challenges.
In this position, you’ll be the primary owner of a recently deployed Azure-based data warehouse, ensuring it continues to evolve to meet the needs of a fast-growing organisation. You’ll partner with colleagues across technology, finance, and data governance to guarantee that data is accurate, secure, and ready to drive informed decisions.
With the platform foundation already in place, your mission will be to scale, optimise, and operationalise it — from designing new integrations to building tools and processes that extract
maximum business value.
Key Responsibilities
- Develop and maintain a roadmap for expanding the Azure data warehouse to support advanced reporting and analytics.
- Enhance and maintain the existing environment, embedding data engineering best practices.
- Design and implement ETL workflows, transformations, and data mapping solutions.
- Monitor and uphold data quality, privacy, and compliance with all relevant regulations.
- Improve performance and scalability while researching emerging data technologies.
- Act as a go-to expert for available datasets and collaborate with teams to design suitable data models.
Essential Skills & Experience
- 5+ years in data engineering, ideally at senior or lead level.
- Strong hands-on experience with Python, Azure Databricks, and Azure Synapse Analytics.
- Advanced SQL skills, including stored procedures and formal database design.
- Proven data modelling capabilities.
- Proficiency with Microsoft Azure data services and CI/CD pipelines.
- Experience integrating data across systems using APIs.
- Analytical mindset and excellent problem-solving abilities.
- Strong communication skills, able to work with both technical and non-technical stakeholders
Desirable Skills
- Knowledge of C#, Logic Apps, or Azure Integration Services.
- Experience with NoSQL or unstructured datasets.
- Familiarity with Power BI for dashboarding and reporting.
- Previous exposure to regulated environments (e.g., GDPR, ISO27001).
If you’re passionate about using modern cloud data technologies to deliver business impact — and want a role where you can directly influence data strategy — we’d love to hear from you.
📩 Apply here: LinkedIn Job Link
#DataEngineering #Azure #DataWarehouse #SQL #Python #Hiring #LondonJobs #AzureDataEngineer
Data Warehouse Solution Engineer employer: MBN Solutions
Contact Detail:
MBN Solutions Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Warehouse Solution Engineer
✨Tip Number 1
Familiarise yourself with Azure data services, especially Azure Databricks and Azure Synapse Analytics. Being able to discuss your hands-on experience with these tools during the interview will demonstrate your technical expertise and readiness for the role.
✨Tip Number 2
Brush up on your SQL skills, particularly in writing stored procedures and database design. Prepare to showcase your ability to create efficient queries and data models, as this is crucial for the responsibilities of the position.
✨Tip Number 3
Network with professionals in the data engineering field, especially those who work with Azure technologies. Engaging in conversations can provide insights into the latest trends and challenges, which you can reference in your discussions with us.
✨Tip Number 4
Prepare examples of how you've previously improved data quality and compliance in your past roles. Being able to articulate your problem-solving abilities and analytical mindset will set you apart from other candidates.
We think you need these skills to ace Data Warehouse Solution Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your relevant experience in data engineering, particularly with Azure, Python, and SQL. Use specific examples to demonstrate your skills in developing ETL workflows and maintaining data quality.
Craft a Compelling Cover Letter: In your cover letter, express your passion for data technologies and how your background aligns with the responsibilities of the Data Warehouse Solution Engineer role. Mention your problem-solving abilities and your experience working with both technical and non-technical stakeholders.
Showcase Relevant Projects: If you have worked on projects involving Azure Databricks or Azure Synapse Analytics, be sure to include these in your application. Describe your role and the impact of your contributions on the project's success.
Highlight Soft Skills: Since strong communication skills are essential for this role, emphasise your ability to collaborate with diverse teams. Provide examples of how you've successfully communicated complex data concepts to non-technical audiences.
How to prepare for a job interview at MBN Solutions
✨Showcase Your Technical Skills
Be prepared to discuss your hands-on experience with Python, Azure Databricks, and Azure Synapse Analytics. Bring examples of past projects where you designed ETL workflows or improved data quality, as this will demonstrate your technical expertise.
✨Understand the Business Impact
Articulate how your work in data engineering can drive business value. Be ready to explain how you've used data to inform decisions in previous roles, and how you plan to do the same in this position.
✨Communicate Effectively
Since you'll be working with both technical and non-technical stakeholders, practice explaining complex concepts in simple terms. This will show that you can bridge the gap between different teams and ensure everyone is on the same page.
✨Prepare for Problem-Solving Questions
Expect to face scenario-based questions that assess your analytical mindset and problem-solving abilities. Think of specific challenges you've encountered in your previous roles and how you overcame them, as this will highlight your critical thinking skills.
