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- Tasks: Design and build scalable data platforms using Azure and Snowflake for enterprise clients.
- Company: Join a global tech consultancy focused on innovative data solutions.
- Benefits: Competitive salary, bonus, hybrid work, and comprehensive health benefits.
- Why this job: Make a real impact by enabling data-driven decisions in a dynamic environment.
- Qualifications: 7+ years in software engineering with strong cloud data platform experience.
- Other info: Collaborative office culture in Central London with excellent career growth opportunities.
The predicted salary is between 43200 - 72000 £ per year.
You will be joining a global technology consultancy to help design and deliver long-term, enterprise-grade data platforms that enable data-driven decision-making across complex, multi-line organizations.
This is a high-impact role within a growing data engineering practice, focused on building modern cloud-based solutions that power analytics, reporting, and business intelligence at scale for enterprise clients.
You will design, build, and optimise a scalable, cloud-native data platform that acts as the foundation for business-critical insight. You will work closely with stakeholders across the business, translating requirements into robust, production-grade data solutions. This is a hands-on engineering role where you will take ownership of pipelines, models, and performance.
- Design, build, and maintain scalable data pipelines in Azure and Snowflake
- Build and enhance enterprise data warehouse models
- Write and optimise complex SQL queries for analytics and reporting
- Ensure data quality, reconciliation, and consistency across multiple sources
- Partner with BI teams to support dashboards and reporting tools
- Continuously improve reliability, scalability, and performance
You will be expected to work from the Central London office three to four days per week to enable close collaboration with technical and business stakeholders.
7+ years software engineering experience, including 5+ years with data-intensive systems
~2+ years hands-on experience with cloud data platforms (Azure preferred)
~ Strong expertise in Azure Data Factory, Azure SQL, Azure Storage, Azure Functions, and Snowflake (1+ year)
~ Advanced SQL skills, including complex ETL and dimensional/data modeling
~ Experience building batch and micro-batch data pipelines
~ Deep understanding of enterprise data warehouse architecture and methodologies
~ Strong analytical mindset with a focus on data quality
Snowflake performance tuning and cost optimisation
Python
End-to-end data platform architecture
Enterprise BI platforms
100,000 base salary + bonus
~ Pension, life assurance, private healthcare and wellness allowance
~25 days holiday plus bank holidays
~ Hybrid working
~ Visa sponsorship and relocation support
Senior Engineer, Data Engineering in London employer: Prism Digital
Contact Detail:
Prism Digital Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Engineer, Data Engineering in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the data engineering field, especially those who work with Azure and Snowflake. A friendly chat can lead to insider info about job openings or even referrals.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your best projects, especially those involving cloud data platforms. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your SQL and data pipeline knowledge. Be ready to discuss your experience with Azure Data Factory and Snowflake, as well as how you've tackled data quality issues in the past.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got some fantastic opportunities waiting for you, and applying directly can sometimes give you an edge. Plus, it’s super easy to keep track of your applications!
We think you need these skills to ace Senior Engineer, Data Engineering in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Senior Data Engineer role. Highlight your experience with Azure, Snowflake, and any relevant data engineering projects. We want to see how your skills align with what we're looking for!
Showcase Your Projects: Include specific examples of projects you've worked on that demonstrate your expertise in building scalable data pipelines and optimising performance. This helps us understand your hands-on experience and problem-solving abilities.
Craft a Compelling Cover Letter: Your cover letter should tell us why you're passionate about data engineering and how you can contribute to our team. Be sure to mention your analytical mindset and focus on data quality, as these are key for us.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows us you're keen to join our team!
How to prepare for a job interview at Prism Digital
✨Know Your Tech Inside Out
Make sure you brush up on your Azure and Snowflake skills. Be ready to discuss specific projects where you've designed and built data pipelines or optimised performance. The interviewers will want to see that you can translate technical jargon into real-world applications.
✨Showcase Your Problem-Solving Skills
Prepare to tackle some scenario-based questions. Think about how you would approach building a scalable data platform or resolving data quality issues. Use examples from your past experience to illustrate your analytical mindset and hands-on engineering capabilities.
✨Understand the Business Context
Since this role involves working closely with stakeholders, demonstrate your understanding of how data-driven decision-making impacts business outcomes. Be ready to discuss how your work in data engineering can support analytics and reporting tools for enterprise clients.
✨Ask Insightful Questions
At the end of the interview, don’t shy away from asking questions. Inquire about the team dynamics, the challenges they face with their current data platforms, or how they measure success in this role. This shows your genuine interest and helps you gauge if the company is the right fit for you.