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- Tasks: Build and maintain scalable data pipelines using Airflow and dbt on AWS.
- Company: Fast-growing B2B financial services business based in London.
- Benefits: Competitive salary, hybrid work model, and opportunities for professional growth.
- Other info: Collaborative Agile/Scrum environment with a focus on data quality and governance.
- Why this job: Tackle interesting engineering challenges while modernising data infrastructure.
- Qualifications: Proven experience in data engineering with strong Python and SQL skills.
The predicted salary is between 75000 - 105000 £ per year.
I'm working with a fast-growing B2B finserv business based in London, and they're looking for a Senior Data Engineer to join their data platform team.
This is a genuinely interesting engineering problem — they're sitting on a large volume of valuable financial data and are in the process of modernising their data infrastructure, moving away from legacy systems towards a scalable, cloud-native stack.
- Building and maintaining scalable data pipelines using Airflow and dbt
- Working across AWS cloud infrastructure
- Collaborating with analysts and data scientists to deliver reliable, clean data for downstream reporting and business decision-making
- Contributing to data quality, governance, and best practices across the team
Proven data engineering experience with strong Python and SQL.
Solid AWS experience.
Comfortable working in Agile/Scrum environments.
Data Engineer (AWS) · Hybrid Remote in City of London employer: Kinvr Digital
Contact Detail:
Kinvr Digital Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer (AWS) · Hybrid Remote in City of London
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, especially those who work with AWS or data engineering. A friendly chat can lead to insider info about job openings that aren't even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Python, SQL, and AWS. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on Agile/Scrum methodologies. Be ready to discuss how you've collaborated with analysts and data scientists in the past. We want to see how you can contribute to a team!
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who take the initiative to connect directly with us.
We think you need these skills to ace Data Engineer (AWS) · Hybrid Remote in City of London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with AWS, Python, and SQL. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re excited about this role and how your background makes you a perfect fit for our data platform team. Keep it engaging and personal!
Showcase Your Problem-Solving Skills: Since we’re tackling interesting engineering problems, share examples of how you've approached challenges in the past. We love seeing your thought process and how you’ve contributed to modernising data infrastructures.
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 don’t miss out on any important updates from our team!
How to prepare for a job interview at Kinvr Digital
✨Know Your Tech Stack
Make sure you’re well-versed in AWS, Python, and SQL. Brush up on your knowledge of Airflow and dbt too, as these are crucial for the role. Being able to discuss how you've used these technologies in past projects will show that you're not just familiar with them, but that you can apply them effectively.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific engineering challenges you've faced and how you tackled them. This could involve modernising data infrastructure or building scalable data pipelines. Use the STAR method (Situation, Task, Action, Result) to structure your answers and highlight your contributions.
✨Understand the Business Context
Since this role is within a B2B financial services company, it’s important to understand the industry. Familiarise yourself with common data challenges in finance and how clean, reliable data impacts business decisions. This will help you connect your technical skills to the company's goals during the interview.
✨Emphasise Collaboration
As you'll be working closely with analysts and data scientists, be ready to discuss your experience in collaborative environments, especially Agile/Scrum. Share examples of how you’ve contributed to team success and maintained data quality and governance, as this will demonstrate your ability to work well within a team.